def loadmln(self, config, mln=None):
if config == 'query': config = self.queryconf
elif config == 'learn': config = self.learnconf
from pracmln.mln.base import parse_mln
path = self.path if hasattr(self, 'path') else None
return parse_mln(self.mlns[ifNone(mln, config['mln'])],
projectpath=path,
logic=config['logic'],
grammar=config['grammar'])
def consistent(self, world, strict=False):
'''
Checks for this variable if its assignment in the assignment `evidence` is consistent.
:param evidence: the assignment to be checked.
:param strict: if True, no unknown assignments are allowed, i.e. there must not be any
ground atoms in the variable that do not have a truth value assigned.
'''
total = 0
evstr = ','.join([ifNone(world[atom.idx], '?', str) for atom in self.gndatoms])
for gnatom in self.gndatoms:
val = world[gnatom.idx]
if strict and val is None:
raise MRFValueException('Not all values have truth assignments: %s: %s' % (repr(self), evstr))
total += ifNone(val, 0)
if not (total == 1 if strict else total in Interval('[0,1]')):
raise MRFValueException('Invalid value of variable %s: %s' % (repr(self), evstr))
return True
def compose(self):
p = '/'.join(self.path)
if self.project is not None:
p += ('/' if p else '') + self.project
if self.file is not None:
p += ':' + str(self.file)
else:
p += ifNone(self.file, '', lambda x: '/' + str(x))
return p
def compose(self):
p = '/'.join(self.path)
if self.project is not None:
p += ('/' if p else '') + self.project
if self.file is not None:
p += ':' + str(self.file)
else:
p += ifNone(self.file, '', lambda x: '/' + str(x))
return p
def noisyor(self, world):
prod = 1.0
for lit in self.children:
p = ifNone(lit(world), 1)
if not lit.negated:
factor = p
else:
factor = 1.0 - p
prod *= 1.0 - factor
return 1.0 - prod
def loaddb(self, mln, config, db=None):
if db is None:
if config == 'query': config = self.queryconf
elif config == 'learn': config = self.learnconf
else: raise Exception('Need a database name or config.')
from pracmln.mln.database import parse_db
path = self.path if hasattr(self, 'path') else None
out(db)
out(self.dbs[db])
return parse_db(mln, self.dbs[ifNone(db, config['db'])], ignore_unknown_preds=config['ignore_unknown_preds'], projectpath=path)
def noisyor(self, world):
prod = 1.0
for lit in self.children:
p = ifNone(lit(world), 1)
if not lit.negated:
factor = p
else:
factor = 1.0 - p
prod *= 1.0 - factor
return 1.0 - prod
def loaddb(self, mln, config, db=None):
if db is None:
if config == 'query': config = self.queryconf
elif config == 'learn': config = self.learnconf
else: raise Exception('Need a database name or config.')
from pracmln.mln.database import parse_db
path = self.path if hasattr(self, 'path') else None
out(db)
out(self.dbs[db])
return parse_db(mln,
self.dbs[ifNone(db, config['db'])],
ignore_unknown_preds=config['ignore_unknown_preds'],
projectpath=path)
def __init__(self, mrf, simplify=False, unsatfailure=False, formulas=None, cache=auto, **params):
self.mrf = mrf
self.formulas = ifNone(formulas, list(self.mrf.formulas))
self.total_gf = 0
for f in self.formulas:
self.total_gf += f.countgroundings(self.mrf)
self.grounder = None
self._cachesize = CACHE_SIZE if cache is auto else cache
self._cache = None
self.__cacheinit = False
self.__cachecomplete = False
self._params = params
self.watch = StopWatch()
self.simplify = simplify
self.unsatfailure = unsatfailure
def __init__(self,
mrf,
simplify=False,
unsatfailure=False,
formulas=None,
cache=auto,
**params):
self.mrf = mrf
self.formulas = ifNone(formulas, list(self.mrf.formulas))
self.total_gf = 0
for f in self.formulas:
self.total_gf += f.countgroundings(self.mrf)
self.grounder = None
self._cachesize = CACHE_SIZE if cache is auto else cache
self._cache = None
self.__cacheinit = False
self.__cachecomplete = False
self._params = params
self.watch = StopWatch()
self.simplify = simplify
self.unsatfailure = unsatfailure
def __init__(self, master, gconf, directory=None):
self.master = master
# icon = Tkinter.Image("photo", file=os.path.join(PRACMLN_HOME, 'doc', '_static', 'favicon.ico'))
# self.master.tk.call('wm', 'iconphoto', self.master._w, icon)
self.initialized = False
self.master.bind('<Return>', self.infer)
self.master.bind('<Escape>', lambda a: self.master.quit())
self.master.protocol('WM_DELETE_WINDOW', self.quit)
self.dir = os.path.abspath(ifNone(directory, ifNone(gconf['prev_query_path'], os.getcwd())))
self.frame = Frame(master)
self.frame.pack(fill=BOTH, expand=1)
self.frame.columnconfigure(1, weight=1)
row = 0
# pracmln project options
Label(self.frame, text='PRACMLN Project: ').grid(row=row, column=0,
sticky='ES')
project_container = Frame(self.frame)
project_container.grid(row=row, column=1, sticky="NEWS")
# new proj file
self.btn_newproj = Button(project_container, text='New Project...', command=self.new_project)
self.btn_newproj.grid(row=0, column=1, sticky="WS")
# open proj file
self.btn_openproj = Button(project_container, text='Open Project...', command=self.ask_load_project)
self.btn_openproj.grid(row=0, column=2, sticky="WS")
# save proj file
self.btn_updateproj = Button(project_container, text='Save Project...', command=self.noask_save_project)
self.btn_updateproj.grid(row=0, column=3, sticky="WS")
# save proj file as...
self.btn_saveproj = Button(project_container, text='Save Project as...', command=self.ask_save_project)
self.btn_saveproj.grid(row=0, column=4, sticky="WS")
# grammar selection
row += 1
Label(self.frame, text='Grammar: ').grid(row=row, column=0, sticky='E')
grammars = ['StandardGrammar', 'PRACGrammar']
self.selected_grammar = StringVar(master)
self.selected_grammar.trace('w', self.settings_setdirty)
l = apply(OptionMenu, (self.frame, self.selected_grammar) + tuple(grammars))
l.grid(row=row, column=1, sticky='NWE')
# logic selection
row += 1
Label(self.frame, text='Logic: ').grid(row=row, column=0, sticky='E')
logics = ['FirstOrderLogic', 'FuzzyLogic']
self.selected_logic = StringVar(master)
self.selected_logic.trace('w', self.settings_setdirty)
l = apply(OptionMenu, (self.frame, self.selected_logic) + tuple(logics))
l.grid(row=row, column=1, sticky='NWE')
# mln section
row += 1
Label(self.frame, text="MLN: ").grid(row=row, column=0, sticky='NE')
self.mln_container = FileEditBar(self.frame, dir=self.dir,
filesettings={'extension': '.mln', 'ftypes': [('MLN files', '.mln')]},
defaultname='*unknown{}',
importhook=self.import_mln,
deletehook=self.delete_mln,
projecthook=self.save_proj,
filecontenthook=self.mlnfilecontent,
fileslisthook=self.mlnfiles,
updatehook=self.update_mln,
onchangehook=self.project_setdirty)
self.mln_container.grid(row=row, column=1, sticky="NEWS")
self.mln_container.columnconfigure(1, weight=2)
self.frame.rowconfigure(row, weight=1)
row += 1
self.use_emln = IntVar()
self.use_emln.set(0)
self.cb_use_emln = Checkbutton(self.frame, text="use model extension",
variable=self.use_emln,
command=self.onchange_use_emln)
self.cb_use_emln.grid(row=row, column=1, sticky="W")
# mln extension section
row += 1
self.emlncontainerrow = row
self.emln_label = Label(self.frame, text="EMLN: ")
self.emln_label.grid(row=self.emlncontainerrow, column=0, sticky='NE')
self.emln_container = FileEditBar(self.frame,
dir=self.dir,
filesettings={'extension': '.emln', 'ftypes': [('MLN extension files','.emln')]},
defaultname='*unknown{}',
importhook=self.import_emln,
deletehook=self.delete_emln,
projecthook=self.save_proj,
filecontenthook=self.emlnfilecontent,
fileslisthook=self.emlnfiles,
updatehook=self.update_emln,
onchangehook=self.project_setdirty)
self.emln_container.grid(row=self.emlncontainerrow, column=1, sticky="NEWS")
self.emln_container.columnconfigure(1, weight=2)
self.onchange_use_emln(dirty=False)
self.frame.rowconfigure(row, weight=1)
# db section
row += 1
Label(self.frame, text="Evidence: ").grid(row=row, column=0, sticky='NE')
self.db_container = FileEditBar(self.frame, dir=self.dir,
filesettings={'extension': '.db', 'ftypes': [('Database files', '.db')]},
defaultname='*unknown{}',
importhook=self.import_db,
deletehook=self.delete_db,
projecthook=self.save_proj,
filecontenthook=self.dbfilecontent,
fileslisthook=self.dbfiles,
updatehook=self.update_db,
onchangehook=self.project_setdirty)
self.db_container.grid(row=row, column=1, sticky="NEWS")
self.db_container.columnconfigure(1, weight=2)
self.frame.rowconfigure(row, weight=1)
# inference method selection
row += 1
self.list_methods_row = row
Label(self.frame, text="Method: ").grid(row=row, column=0, sticky=E)
self.selected_method = StringVar(master)
self.selected_method.trace('w', self.select_method)
methodnames = sorted(InferenceMethods.names())
self.list_methods = apply(OptionMenu, (self.frame, self.selected_method) + tuple(methodnames))
self.list_methods.grid(row=self.list_methods_row, column=1, sticky="NWE")
# options
row += 1
option_container = Frame(self.frame)
option_container.grid(row=row, column=1, sticky="NEWS")
# Multiprocessing
self.multicore = IntVar()
self.cb_multicore = Checkbutton(option_container, text="Use all CPUs",
variable=self.multicore,
command=self.settings_setdirty)
self.cb_multicore.grid(row=0, column=2, sticky=W)
# profiling
self.profile = IntVar()
self.cb_profile = Checkbutton(option_container, text='Use Profiler',
variable=self.profile,
command=self.settings_setdirty)
self.cb_profile.grid(row=0, column=3, sticky=W)
# verbose
self.verbose = IntVar()
self.cb_verbose = Checkbutton(option_container, text='verbose',
variable=self.verbose,
command=self.settings_setdirty)
self.cb_verbose.grid(row=0, column=4, sticky=W)
# options
self.ignore_unknown_preds = IntVar(master)
self.cb_ignore_unknown_preds = Checkbutton(option_container,
text='ignore unkown predicates',
variable=self.ignore_unknown_preds,
command=self.settings_setdirty)
self.cb_ignore_unknown_preds.grid(row=0, column=5, sticky="W")
# queries
row += 1
Label(self.frame, text="Queries: ").grid(row=row, column=0, sticky=E)
self.query = StringVar(master)
self.query.trace('w', self.settings_setdirty)
Entry(self.frame, textvariable=self.query).grid(row=row, column=1, sticky="NEW")
# additional parameters
row += 1
Label(self.frame, text="Add. params: ").grid(row=row, column=0, sticky="NE")
self.params = StringVar(master)
self.params.trace('w', self.settings_setdirty)
self.entry_params = Entry(self.frame, textvariable=self.params)
self.entry_params.grid(row=row, column=1, sticky="NEW")
# closed-world predicates
row += 1
Label(self.frame, text="CW preds: ").grid(row=row, column=0, sticky="E")
cw_container = Frame(self.frame)
cw_container.grid(row=row, column=1, sticky='NEWS')
cw_container.columnconfigure(0, weight=1)
self.cwPreds = StringVar(master)
self.cwPreds.trace('w', self.settings_setdirty)
self.entry_cw = Entry(cw_container, textvariable=self.cwPreds)
self.entry_cw.grid(row=0, column=0, sticky="NEWS")
self.closed_world = IntVar()
self.cb_closed_world = Checkbutton(cw_container, text="CW Assumption",
variable=self.closed_world,
command=self.onchange_cw)
self.cb_closed_world.grid(row=0, column=1, sticky='W')
# output filename
row += 1
output_cont = Frame(self.frame)
output_cont.grid(row=row, column=1, sticky='NEWS')
output_cont.columnconfigure(0, weight=1)
# - filename
Label(self.frame, text="Output: ").grid(row=row, column=0, sticky="NE")
self.output_filename = StringVar(master)
self.entry_output_filename = Entry(output_cont, textvariable=self.output_filename)
self.entry_output_filename.grid(row=0, column=0, sticky="NEW")
# - save option
self.save = IntVar()
self.cb_save = Checkbutton(output_cont, text="save", variable=self.save)
self.cb_save.grid(row=0, column=1, sticky=W)
# start button
row += 1
start_button = Button(self.frame, text=">> Start Inference <<", command=self.infer)
start_button.grid(row=row, column=1, sticky="NEW")
self.settings_dirty = IntVar()
self.project_dirty = IntVar()
self.gconf = gconf
self.project = None
self.project_dir = os.path.abspath(ifNone(directory, ifNone(gconf['prev_query_path'], os.getcwd())))
if gconf['prev_query_project': self.project_dir] is not None:
self.load_project(os.path.join(self.project_dir, gconf['prev_query_project':self.project_dir]))
else:
self.new_project()
self.config = self.project.queryconf
self.project.addlistener(self.project_setdirty)
self.mln_container.dirty = False
self.emln_container.dirty = False
self.db_container.dirty = False
self.project_setdirty(dirty=False)
self.master.geometry(gconf['window_loc_query'])
self.initialized = True
def exists(self):
'''
Checks if the file exists.
'''
return os.path.exists(
os.path.join(self.resolve_path(), ifNone(self.project, self.file)))
def set_config(self, newconf):
self.config = newconf
self.selected_grammar.set(ifNone(newconf.get('grammar'), 'PRACGrammar'))
self.selected_logic.set(ifNone(newconf.get('logic'), 'FirstOrderLogic'))
self.mln_container.selected_file.set(ifNone(newconf.get('mln'), ''))
if self.use_emln.get():
self.emln_container.selected_file.set(ifNone(newconf.get('mln'), ''))
self.db_container.selected_file.set(ifNone(newconf.get('db'), ""))
self.selected_method.set(ifNone(newconf.get("method"), InferenceMethods.name('MCSAT'), transform=InferenceMethods.name))
self.multicore.set(ifNone(newconf.get('multicore'), 0))
self.profile.set(ifNone(newconf.get('profile'), 0))
self.params.set(ifNone(newconf.get('params'), ''))
self.use_emln.set(ifNone(newconf.get('use_emln'), 0))
self.verbose.set(ifNone(newconf.get('verbose'), 1))
self.ignore_unknown_preds.set(ifNone(newconf.get('ignore_unknown_preds'), 0))
self.output_filename.set(ifNone(newconf.get('output_filename'), ''))
self.cwPreds.set(ifNone(newconf.get('cw_preds'), ''))
self.closed_world.set(ifNone(newconf.get('cw'), 0))
self.save.set(ifNone(newconf.get('save'), 0))
self.query.set(ifNone(newconf.get('queries'), ''))
self.onchange_cw()
def loadmln(self, config, mln=None):
if config == 'query': config = self.queryconf
elif config == 'learn': config = self.learnconf
from pracmln.mln.base import parse_mln
path = self.path if hasattr(self, 'path') else None
return parse_mln(self.mlns[ifNone(mln, config['mln'])], projectpath=path, logic=config['logic'], grammar=config['grammar'])
def exists(self):
'''
Checks if the file exists.
'''
return os.path.exists(os.path.join(self.resolve_path(), ifNone(self.project, self.file)))
def set_config(self, conf):
self.config = conf
self.selected_grammar.set(ifNone(conf.get('grammar'), 'PRACGrammar'))
self.selected_logic.set(ifNone(conf.get('logic'), 'FirstOrderLogic'))
self.mln_container.selected_file.set(ifNone(conf.get('mln'), ''))
if self.use_emln.get():
self.emln_container.selected_file.set(ifNone(conf.get('mln'), ''))
self.db_container.selected_file.set(ifNone(conf.get('db'), ""))
self.selected_method.set(
ifNone(conf.get("method"),
InferenceMethods.name('MCSAT'),
transform=InferenceMethods.name))
self.multicore.set(ifNone(conf.get('multicore'), 0))
self.profile.set(ifNone(conf.get('profile'), 0))
self.params.set(ifNone(conf.get('params'), ''))
self.use_emln.set(ifNone(conf.get('use_emln'), 0))
self.verbose.set(ifNone(conf.get('verbose'), 1))
self.ignore_unknown_preds.set(
ifNone(conf.get('ignore_unknown_preds'), 0))
self.output_filename.set(ifNone(conf.get('output_filename'), ''))
self.cwPreds.set(ifNone(conf.get('cw_preds'), ''))
self.closed_world.set(ifNone(conf.get('cw'), 0))
self.save.set(ifNone(conf.get('save'), 0))
self.query.set(ifNone(conf.get('queries'), ''))
self.onchange_cw()
def __init__(self, master, gconf, directory=None):
self.master = master
# icon = Tkinter.Image("photo", file=os.path.join(PRACMLN_HOME,
# 'doc',
# '_static',
# 'favicon.ico'))
# self.master.tk.call('wm', 'iconphoto', self.master._w, icon)
self.initialized = False
self.master.bind('<Return>', self.learn)
self.master.bind('<Escape>', lambda a: self.master.quit())
self.master.protocol('WM_DELETE_WINDOW', self.quit)
# logo = Label(self.master, image=img)
# logo.pack(side = "right", anchor='ne')
self.dir = os.path.abspath(ifNone(directory, ifNone(gconf['prev_learnwts_path'], os.getcwd())))
self.frame = Frame(master)
self.frame.pack(fill=BOTH, expand=1)
self.frame.columnconfigure(1, weight=1)
row = 0
# pracmln project options
Label(self.frame, text='PRACMLN Project: ').grid(row=row, column=0,
sticky='ES')
project_container = Frame(self.frame)
project_container.grid(row=row, column=1, sticky="NEWS")
# new proj file
self.btn_newproj = Button(project_container, text='New Project...',
command=self.new_project)
self.btn_newproj.grid(row=0, column=1, sticky="WS")
# open proj file
self.btn_openproj = Button(project_container, text='Open Project...',
command=self.ask_load_project)
self.btn_openproj.grid(row=0, column=2, sticky="WS")
# save proj file
self.btn_saveproj = Button(project_container, text='Save Project',
command=self.noask_save_project)
self.btn_saveproj.grid(row=0, column=3, sticky="WS")
# save proj file as...
self.btn_saveproj = Button(project_container,
text='Save Project as...',
command=self.ask_save_project)
self.btn_saveproj.grid(row=0, column=4, sticky="WS")
# grammar selection
row += 1
Label(self.frame, text='Grammar: ').grid(row=row, column=0, sticky='E')
grammars = ['StandardGrammar', 'PRACGrammar']
self.selected_grammar = StringVar(master)
self.selected_grammar.trace('w', self.settings_setdirty)
l = apply(OptionMenu,
(self.frame, self.selected_grammar) + tuple(grammars))
l.grid(row=row, column=1, sticky='NWE')
# logic selection
row += 1
Label(self.frame, text='Logic: ').grid(row=row, column=0, sticky='E')
logics = ['FirstOrderLogic', 'FuzzyLogic']
self.selected_logic = StringVar(master)
self.selected_logic.trace('w', self.settings_setdirty)
l = apply(OptionMenu,
(self.frame, self.selected_logic) + tuple(logics))
l.grid(row=row, column=1, sticky='NWE')
# mln section
row += 1
Label(self.frame, text="MLN: ").grid(row=row, column=0, sticky='NE')
self.mln_container = FileEditBar(self.frame, dir=self.dir,
filesettings={'extension': '.mln', 'ftypes': [('MLN files', '.mln')]},
defaultname='*unknown{}',
importhook=self.import_mln,
deletehook=self.delete_mln,
projecthook=self.save_proj,
filecontenthook=self.mlnfilecontent,
fileslisthook=self.mlnfiles,
updatehook=self.update_mln,
onchangehook=self.project_setdirty)
self.mln_container.grid(row=row, column=1, sticky="NEWS")
self.mln_container.columnconfigure(1, weight=2)
self.frame.rowconfigure(row, weight=1)
# method selection
row += 1
Label(self.frame, text="Method: ").grid(row=row, column=0, sticky=E)
self.selected_method = StringVar(master)
methodnames = sorted(LearningMethods.names())
self.list_methods = apply(OptionMenu, (self.frame, self.selected_method) + tuple(methodnames))
self.list_methods.grid(row=row, column=1, sticky="NWE")
self.selected_method.trace("w", self.select_method)
# additional parametrization
row += 1
frame = Frame(self.frame)
frame.grid(row=row, column=1, sticky="NEW")
# use prior
self.use_prior = IntVar()
self.cb_use_prior = Checkbutton(frame, text="use prior with mean of ",
variable=self.use_prior,
command=self.onchange_useprior)
self.cb_use_prior.pack(side=LEFT)
# set prior
self.priorMean = StringVar(master)
self.en_prior_mean = Entry(frame, textvariable=self.priorMean, width=5)
self.en_prior_mean.pack(side=LEFT)
self.priorMean.trace('w', self.settings_setdirty)
Label(frame, text="and std dev of").pack(side=LEFT)
# std. dev.
self.priorStdDev = StringVar(master)
self.en_stdev = Entry(frame, textvariable=self.priorStdDev, width=5)
self.priorStdDev.trace('w', self.settings_setdirty)
self.en_stdev.pack(side=LEFT)
# use initial weights in MLN
self.use_initial_weights = IntVar()
self.cb_use_initial_weights = Checkbutton(frame,
text="use initial weights",
variable=self.use_initial_weights,
command=self.settings_setdirty)
self.cb_use_initial_weights.pack(side=LEFT)
# use incremental learning
self.incremental = IntVar()
self.cb_incremental = Checkbutton(frame, text="learn incrementally",
variable=self.incremental,
command=self.onchange_incremental)
self.cb_incremental.pack(side=LEFT)
# shuffle databases
self.shuffle = IntVar()
self.cb_shuffle = Checkbutton(frame, text="shuffle databases",
variable=self.shuffle, state='disabled')
self.cb_shuffle.pack(side=LEFT)
# discriminative learning settings
row += 1
self.discrPredicates = IntVar()
self.discrPredicates.trace('w', self.change_discr_preds)
self.discrPredicates.set(1)
frame = Frame(self.frame)
frame.grid(row=row, column=1, sticky="NEWS")
self.rbQueryPreds = Radiobutton(frame, text="Query preds:",
variable=self.discrPredicates,
value=QUERY_PREDS)
self.rbQueryPreds.grid(row=0, column=0, sticky="NE")
self.queryPreds = StringVar(master)
frame.columnconfigure(1, weight=1)
self.entry_nePreds = Entry(frame, textvariable=self.queryPreds)
self.entry_nePreds.grid(row=0, column=1, sticky="NEW")
self.rbEvidencePreds = Radiobutton(frame, text='Evidence preds',
variable=self.discrPredicates,
value=EVIDENCE_PREDS)
self.rbEvidencePreds.grid(row=0, column=2, sticky='NEWS')
self.evidencePreds = StringVar(master)
self.entryEvidencePreds = Entry(frame, textvariable=self.evidencePreds)
self.entryEvidencePreds.grid(row=0, column=3, sticky='NEWS')
# db section
row += 1
Label(self.frame, text="Evidence: ").grid(row=row, column=0, sticky='NE')
self.db_container = FileEditBar(self.frame, dir=self.dir,
filesettings={'extension': '.db', 'ftypes': [('Database files', '.db')]},
defaultname='*unknown{}',
importhook=self.import_db,
deletehook=self.delete_db,
projecthook=self.save_proj,
filecontenthook=self.dbfilecontent,
fileslisthook=self.dbfiles,
updatehook=self.update_db,
onchangehook=self.project_setdirty)
self.db_container.grid(row=row, column=1, sticky="NEWS")
self.db_container.columnconfigure(1, weight=2)
self.frame.rowconfigure(row, weight=1)
# file patterns
row += 1
frame = Frame(self.frame)
frame.grid(row=row, column=1, sticky="NEW")
col = 0
Label(frame, text="OR file pattern:").grid(row=0, column=col, sticky="W")
# - pattern entry
col += 1
frame.columnconfigure(col, weight=1)
self.pattern = StringVar(master)
self.pattern.trace('w', self.onchange_pattern)
self.entry_pattern = Entry(frame, textvariable=self.pattern)
self.entry_pattern.grid(row=0, column=col, sticky="NEW")
# add. parameters
row += 1
Label(self.frame, text="Add. Params: ").grid(row=row, column=0, sticky="E")
self.params = StringVar(master)
Entry(self.frame, textvariable=self.params).grid(row=row, column=1, sticky="NEW")
# options
row += 1
Label(self.frame, text="Options: ").grid(row=row, column=0, sticky="E")
option_container = Frame(self.frame)
option_container.grid(row=row, column=1, sticky="NEWS")
# multicore
self.multicore = IntVar()
self.cb_multicore = Checkbutton(option_container, text="Use all CPUs",
variable=self.multicore,
command=self.settings_setdirty)
self.cb_multicore.grid(row=0, column=1, sticky=E)
# profiling
self.profile = IntVar()
self.cb_profile = Checkbutton(option_container, text='Use Profiler',
variable=self.profile,
command=self.settings_setdirty)
self.cb_profile.grid(row=0, column=3, sticky=W)
# verbose
self.verbose = IntVar()
self.cb_verbose = Checkbutton(option_container, text='verbose',
variable=self.verbose,
command=self.settings_setdirty)
self.cb_verbose.grid(row=0, column=4, sticky=W)
self.ignore_zero_weight_formulas = IntVar()
self.cb_ignore_zero_weight_formulas = Checkbutton(option_container, text='remove 0-weight formulas',
variable=self.ignore_zero_weight_formulas, command=self.settings_setdirty)
self.cb_ignore_zero_weight_formulas.grid(row=0, column=5, sticky=W)
# ignore unknown preds
self.ignore_unknown_preds = IntVar(master)
self.ignore_unknown_preds.trace('w', self.settings_setdirty)
self.cb_ignore_unknown_preds = \
Checkbutton(option_container, text='ignore unkown predicates', variable=self.ignore_unknown_preds)
self.cb_ignore_unknown_preds.grid(row=0, column=6, sticky="W")
row += 1
output_cont = Frame(self.frame)
output_cont.grid(row=row, column=1, sticky='NEWS')
output_cont.columnconfigure(0, weight=1)
Label(self.frame, text="Output: ").grid(row=row, column=0, sticky="E")
self.output_filename = StringVar(master)
self.entry_output_filename = Entry(output_cont, textvariable=self.output_filename)
self.entry_output_filename.grid(row=0, column=0, sticky="EW")
self.save = IntVar(self.master)
self.cb_save = Checkbutton(output_cont, text='save', variable=self.save)
self.cb_save.grid(row=0, column=1, sticky='W')
row += 1
learn_button = Button(self.frame, text=" >> Start Learning << ", command=self.learn)
learn_button.grid(row=row, column=1, sticky="EW")
self.settings_dirty = IntVar()
self.project_dirty = IntVar()
self.gconf = gconf
self.project = None
self.project_dir = os.path.abspath(ifNone(directory, ifNone(gconf['prev_learnwts_path'], os.getcwd())))
if gconf['prev_learnwts_project': self.project_dir] is not None:
self.load_project(os.path.join(self.project_dir, gconf['prev_learnwts_project':self.project_dir]))
else:
self.new_project()
self.config = self.project.learnconf
self.project.addlistener(self.project_setdirty)
self.mln_container.dirty = False
self.db_container.dirty = False
self.project_setdirty(dirty=False)
self.master.geometry(gconf['window_loc_learn'])
self.initialized = True
def __init__(self, master, gconf, directory=None):
self.master = master
# icon = Tkinter.Image("photo", file=os.path.join(PRACMLN_HOME, 'doc', '_static', 'favicon.ico'))
# self.master.tk.call('wm', 'iconphoto', self.master._w, icon)
self.initialized = False
self.master.bind('<Return>', self.infer)
self.master.bind('<Escape>', lambda a: self.master.quit())
self.master.protocol('WM_DELETE_WINDOW', self.quit)
self.dir = os.path.abspath(
ifNone(directory, ifNone(gconf['prev_query_path'], os.getcwd())))
self.frame = Frame(master)
self.frame.pack(fill=BOTH, expand=1)
self.frame.columnconfigure(1, weight=1)
row = 0
# pracmln project options
Label(self.frame, text='PRACMLN Project: ').grid(row=row,
column=0,
sticky='ES')
project_container = Frame(self.frame)
project_container.grid(row=row, column=1, sticky="NEWS")
# new proj file
self.btn_newproj = Button(project_container,
text='New Project...',
command=self.new_project)
self.btn_newproj.grid(row=0, column=1, sticky="WS")
# open proj file
self.btn_openproj = Button(project_container,
text='Open Project...',
command=self.ask_load_project)
self.btn_openproj.grid(row=0, column=2, sticky="WS")
# save proj file
self.btn_updateproj = Button(project_container,
text='Save Project...',
command=self.noask_save_project)
self.btn_updateproj.grid(row=0, column=3, sticky="WS")
# save proj file as...
self.btn_saveproj = Button(project_container,
text='Save Project as...',
command=self.ask_save_project)
self.btn_saveproj.grid(row=0, column=4, sticky="WS")
# grammar selection
row += 1
Label(self.frame, text='Grammar: ').grid(row=row, column=0, sticky='E')
grammars = ['StandardGrammar', 'PRACGrammar']
self.selected_grammar = StringVar(master)
self.selected_grammar.trace('w', self.settings_setdirty)
l = apply(OptionMenu,
(self.frame, self.selected_grammar) + tuple(grammars))
l.grid(row=row, column=1, sticky='NWE')
# logic selection
row += 1
Label(self.frame, text='Logic: ').grid(row=row, column=0, sticky='E')
logics = ['FirstOrderLogic', 'FuzzyLogic']
self.selected_logic = StringVar(master)
self.selected_logic.trace('w', self.settings_setdirty)
l = apply(OptionMenu,
(self.frame, self.selected_logic) + tuple(logics))
l.grid(row=row, column=1, sticky='NWE')
# mln section
row += 1
Label(self.frame, text="MLN: ").grid(row=row, column=0, sticky='NE')
self.mln_container = FileEditBar(self.frame,
dir=self.dir,
filesettings={
'extension': '.mln',
'ftypes': [('MLN files', '.mln')]
},
defaultname='*unknown{}',
importhook=self.import_mln,
deletehook=self.delete_mln,
projecthook=self.save_proj,
filecontenthook=self.mlnfilecontent,
fileslisthook=self.mlnfiles,
updatehook=self.update_mln,
onchangehook=self.project_setdirty)
self.mln_container.grid(row=row, column=1, sticky="NEWS")
self.mln_container.columnconfigure(1, weight=2)
self.frame.rowconfigure(row, weight=1)
row += 1
self.use_emln = IntVar()
self.use_emln.set(0)
self.cb_use_emln = Checkbutton(self.frame,
text="use model extension",
variable=self.use_emln,
command=self.onchange_use_emln)
self.cb_use_emln.grid(row=row, column=1, sticky="W")
# mln extension section
row += 1
self.emlncontainerrow = row
self.emln_label = Label(self.frame, text="EMLN: ")
self.emln_label.grid(row=self.emlncontainerrow, column=0, sticky='NE')
self.emln_container = FileEditBar(self.frame,
dir=self.dir,
filesettings={
'extension':
'.emln',
'ftypes':
[('MLN extension files', '.emln')
]
},
defaultname='*unknown{}',
importhook=self.import_emln,
deletehook=self.delete_emln,
projecthook=self.save_proj,
filecontenthook=self.emlnfilecontent,
fileslisthook=self.emlnfiles,
updatehook=self.update_emln,
onchangehook=self.project_setdirty)
self.emln_container.grid(row=self.emlncontainerrow,
column=1,
sticky="NEWS")
self.emln_container.columnconfigure(1, weight=2)
self.onchange_use_emln(dirty=False)
self.frame.rowconfigure(row, weight=1)
# db section
row += 1
Label(self.frame, text="Evidence: ").grid(row=row,
column=0,
sticky='NE')
self.db_container = FileEditBar(self.frame,
dir=self.dir,
filesettings={
'extension': '.db',
'ftypes':
[('Database files', '.db')]
},
defaultname='*unknown{}',
importhook=self.import_db,
deletehook=self.delete_db,
projecthook=self.save_proj,
filecontenthook=self.dbfilecontent,
fileslisthook=self.dbfiles,
updatehook=self.update_db,
onchangehook=self.project_setdirty)
self.db_container.grid(row=row, column=1, sticky="NEWS")
self.db_container.columnconfigure(1, weight=2)
self.frame.rowconfigure(row, weight=1)
# inference method selection
row += 1
self.list_methods_row = row
Label(self.frame, text="Method: ").grid(row=row, column=0, sticky=E)
self.selected_method = StringVar(master)
self.selected_method.trace('w', self.select_method)
methodnames = sorted(InferenceMethods.names())
self.list_methods = apply(OptionMenu,
(self.frame, self.selected_method) +
tuple(methodnames))
self.list_methods.grid(row=self.list_methods_row,
column=1,
sticky="NWE")
# options
row += 1
option_container = Frame(self.frame)
option_container.grid(row=row, column=1, sticky="NEWS")
# Multiprocessing
self.multicore = IntVar()
self.cb_multicore = Checkbutton(option_container,
text="Use all CPUs",
variable=self.multicore,
command=self.settings_setdirty)
self.cb_multicore.grid(row=0, column=2, sticky=W)
# profiling
self.profile = IntVar()
self.cb_profile = Checkbutton(option_container,
text='Use Profiler',
variable=self.profile,
command=self.settings_setdirty)
self.cb_profile.grid(row=0, column=3, sticky=W)
# verbose
self.verbose = IntVar()
self.cb_verbose = Checkbutton(option_container,
text='verbose',
variable=self.verbose,
command=self.settings_setdirty)
self.cb_verbose.grid(row=0, column=4, sticky=W)
# options
self.ignore_unknown_preds = IntVar(master)
self.cb_ignore_unknown_preds = Checkbutton(
option_container,
text='ignore unkown predicates',
variable=self.ignore_unknown_preds,
command=self.settings_setdirty)
self.cb_ignore_unknown_preds.grid(row=0, column=5, sticky="W")
# queries
row += 1
Label(self.frame, text="Queries: ").grid(row=row, column=0, sticky=E)
self.query = StringVar(master)
self.query.trace('w', self.settings_setdirty)
Entry(self.frame, textvariable=self.query).grid(row=row,
column=1,
sticky="NEW")
# additional parameters
row += 1
Label(self.frame, text="Add. params: ").grid(row=row,
column=0,
sticky="NE")
self.params = StringVar(master)
self.params.trace('w', self.settings_setdirty)
self.entry_params = Entry(self.frame, textvariable=self.params)
self.entry_params.grid(row=row, column=1, sticky="NEW")
# closed-world predicates
row += 1
Label(self.frame, text="CW preds: ").grid(row=row,
column=0,
sticky="E")
cw_container = Frame(self.frame)
cw_container.grid(row=row, column=1, sticky='NEWS')
cw_container.columnconfigure(0, weight=1)
self.cwPreds = StringVar(master)
self.cwPreds.trace('w', self.settings_setdirty)
self.entry_cw = Entry(cw_container, textvariable=self.cwPreds)
self.entry_cw.grid(row=0, column=0, sticky="NEWS")
self.closed_world = IntVar()
self.cb_closed_world = Checkbutton(cw_container,
text="CW Assumption",
variable=self.closed_world,
command=self.onchange_cw)
self.cb_closed_world.grid(row=0, column=1, sticky='W')
# output filename
row += 1
output_cont = Frame(self.frame)
output_cont.grid(row=row, column=1, sticky='NEWS')
output_cont.columnconfigure(0, weight=1)
# - filename
Label(self.frame, text="Output: ").grid(row=row, column=0, sticky="NE")
self.output_filename = StringVar(master)
self.entry_output_filename = Entry(output_cont,
textvariable=self.output_filename)
self.entry_output_filename.grid(row=0, column=0, sticky="NEW")
# - save option
self.save = IntVar()
self.cb_save = Checkbutton(output_cont,
text="save",
variable=self.save)
self.cb_save.grid(row=0, column=1, sticky=W)
# start button
row += 1
start_button = Button(self.frame,
text=">> Start Inference <<",
command=self.infer)
start_button.grid(row=row, column=1, sticky="NEW")
self.settings_dirty = IntVar()
self.project_dirty = IntVar()
self.gconf = gconf
self.project = None
self.project_dir = os.path.abspath(
ifNone(directory, ifNone(gconf['prev_query_path'], os.getcwd())))
if gconf['prev_query_project':self.project_dir] is not None:
self.load_project(
os.path.join(self.project_dir,
gconf['prev_query_project':self.project_dir]))
else:
self.new_project()
self.config = self.project.queryconf
self.project.addlistener(self.project_setdirty)
self.mln_container.dirty = False
self.emln_container.dirty = False
self.db_container.dirty = False
self.project_setdirty(dirty=False)
self.master.geometry(gconf['window_loc_query'])
self.initialized = True
def parse_mln(text, searchpaths=['.'], projectpath=None, logic='FirstOrderLogic', grammar='PRACGrammar', mln=None):
'''
Reads an MLN from a stream providing a 'read' method.
'''
dirs = [os.path.abspath(os.path.expandvars(os.path.expanduser(p))) for p in searchpaths]
formulatemplates = []
text = str(text)
if text == "":
raise MLNParsingError("No MLN content to construct model from was given; must specify either file/list of files or content string!")
# replace some meta-directives in comments
text = re.compile(r'//\s*<group>\s*$', re.MULTILINE).sub("#group", text)
text = re.compile(r'//\s*</group>\s*$', re.MULTILINE).sub("#group.", text)
# remove comments
text = stripComments(text)
if mln is None:
mln = MLN(logic, grammar)
# read lines
mln.hard_formulas = []
templateIdx2GroupIdx = {}
inGroup = False
idxGroup = -1
fixWeightOfNextFormula = False
fuzzy = False
pseudofuzzy = False
uniquevars = None
fixedWeightTemplateIndices = []
lines = text.split("\n")
iLine = 0
while iLine < len(lines):
line = lines[iLine]
iLine += 1
line = line.strip()
try:
if len(line) == 0: continue
# meta directives
if line == "#group":
idxGroup += 1
inGroup = True
continue
elif line == "#group.":
inGroup = False
continue
elif line.startswith("#fixweight"):
fixWeightOfNextFormula = True
continue
elif line.startswith('#fuzzy'):
if not isinstance(mln.logic, FuzzyLogic):
logger.warning('Fuzzy declarations are not supported in %s. Treated as a binary predicate.' % mln.logic.__class__.__name__)
pseudofuzzy = True
else:
fuzzy = True
continue
elif line.startswith("#include"):
filename = line[len("#include "):].strip()
m = re.match(r'"(?P<filename>.+)"', filename)
if m is not None:
filename = m.group('filename')
# if the path is relative, look for the respective file
# relatively to all paths specified. Take the first file matching.
if not mlnpath(filename).exists:
includefilename = None
for d in dirs:
mlnp = '/'.join([d, filename])
if mlnpath(mlnp).exists:
includefilename = mlnp
break
if includefilename is None:
raise Exception('File not found: %s' % filename)
else:
includefilename = filename
else:
m = re.match(r'<(?P<filename>.+)>', filename)
if m is not None:
filename = m.group('filename')
else:
raise MLNParsingError('Malformed #include statement: %s' % line)
if projectpath is None:
raise MLNParsingError('No project specified: Cannot locate import from project: %s' % filename)
includefilename = ':'.join([projectpath, filename])
logger.debug('Including file: "%s"' % includefilename)
p = mlnpath(includefilename)
parse_mln(text=mlnpath(includefilename).content, searchpaths=[p.resolve_path()]+dirs,
projectpath=ifNone(p.project, projectpath, lambda x: '/'.join(p.path+[x])),
logic=logic, grammar=grammar, mln=mln)
continue
elif line.startswith('#unique'):
try:
uniVars = re.search('#unique{(.+)}', line)
uniVars = uniVars.groups()[0]
uniVars = map(str.strip, uniVars.split(','))
uniquevars = uniVars
except:
raise MLNParsingError('Malformed #unique expression: "%s"' % line)
continue
elif line.startswith("#AdaptiveMLNDependency"): # declared as "#AdaptiveMLNDependency:pred:domain"; seems to be deprecated
depPredicate, domain = line.split(":")[1:3]
if hasattr(mln, 'AdaptiveDependencyMap'):
if depPredicate in mln.AdaptiveDependencyMap:
mln.AdaptiveDependencyMap[depPredicate].add(domain)
else:
mln.AdaptiveDependencyMap[depPredicate] = set([domain])
else:
mln.AdaptiveDependencyMap = {depPredicate:set([domain])}
continue
# domain decl
if '=' in line:
# try normal domain definition
parse = mln.logic.parse_domain(line)
if parse is not None:
domName, constants = parse
domName = str(domName)
constants = map(str, constants)
if domName in mln.domains:
logger.debug("Domain redefinition: Domain '%s' is being updated with values %s." % (domName, str(constants)))
if domName not in mln.domains:
mln.domains[domName] = []
mln.constant(domName, *constants)
mln.domain_decls.append(line)
continue
# prior probability requirement
if line.startswith("P("):
m = re.match(r"P\((.*?)\)\s*=\s*([\.\de]+)", line)
if m is None:
raise MLNParsingError("Prior probability constraint formatted incorrectly: %s" % line)
mln.prior(f=mln.logic.parse_formula(m.group(1)), p=float(m.group(2)))
continue
# posterior probability requirement/soft evidence
if line.startswith("R(") or line.startswith("SE("):
m = re.match(r"(?:R|SE)\((.*?)\)\s*=\s*([\.\de]+)", line)
if m is None:
raise MLNParsingError("Posterior probability constraint formatted incorrectly: %s" % line)
mln.posterior(f=mln.logic.parse_formula(m.group(1)), p=float(m.group(2)))
continue
# variable definition
if re.match(r'(\$\w+)\s*=(.+)', line):
m = re.match(r'(\$\w+)\s*=(.+)', line)
if m is None:
raise MLNParsingError("Variable assigment malformed: %s" % line)
mln.vars[m.group(1)] = "%s" % m.group(2).strip()
continue
# predicate decl or formula with weight
else:
isHard = False
isPredDecl = False
if line[ -1] == '.': # hard (without explicit weight -> determine later)
isHard = True
formula = line[:-1]
else: # with weight
# try predicate declaration
isPredDecl = True
try:
pred = mln.logic.parse_predicate(line)
except Exception, e:
isPredDecl = False
if isPredDecl:
predname = str(pred[0])
argdoms = map(str, pred[1])
softmutex = False
mutex = None
for i, dom in enumerate(argdoms):
if dom[-1] in ('!', '?'):
if mutex is not None:
raise Exception('More than one arguments are specified as (soft-)functional')
if fuzzy: raise Exception('(Soft-)functional predicates must not be fuzzy.')
mutex = i
if dom[-1] == '?': softmutex = True
argdoms = map(lambda x: x.strip('!?'), argdoms)
pred = None
if mutex is not None:
if softmutex:
pred = SoftFunctionalPredicate(predname, argdoms, mutex)
else:
pred = FunctionalPredicate(predname, argdoms, mutex)
elif fuzzy:
pred = FuzzyPredicate(predname, argdoms)
fuzzy = False
else:
pred = Predicate(predname, argdoms)
if pseudofuzzy:
mln.fuzzypreds.append(predname)
pseudofuzzy = False
mln.predicate(pred)
continue
else:
# formula (template) with weight or terminated by '.'
if not isHard:
spacepos = line.find(' ')
weight = line[:spacepos]
formula = line[spacepos:].strip()
try:
formula = mln.logic.parse_formula(formula)
if isHard:
weight = HARD # not set until instantiation when other weights are known
idxTemplate = len(formulatemplates)
formulatemplates.append(formula)
fixweight = False
if inGroup:
templateIdx2GroupIdx[idxTemplate] = idxGroup
if fixWeightOfNextFormula == True:
fixWeightOfNextFormula = False
fixweight = True
fixedWeightTemplateIndices.append(idxTemplate)
# expand predicate groups
for variant in formula.expandgrouplits():
mln.formula(variant, weight=weight,
fixweight=fixweight,
unique_templvars=uniquevars)
if uniquevars:
uniquevars = None
except ParseException, e:
raise MLNParsingError("Error parsing formula '%s'\n" % formula)
if fuzzy and not isPredDecl: raise Exception('"#fuzzy" decorator not allowed at this place: %s' % line)
def set_config(self, newconf):
self.config = newconf
self.selected_grammar.set(ifNone(newconf.get('grammar'), 'PRACGrammar'))
self.selected_logic.set(ifNone(newconf.get('logic'), 'FirstOrderLogic'))
self.mln_container.selected_file.set(ifNone(newconf.get('mln'), ''))
self.db_container.selected_file.set(ifNone(newconf.get('db'), ""))
self.selected_method.set(ifNone(newconf.get("method"), LearningMethods.name('BPLL'), transform=LearningMethods.name))
self.pattern.set(ifNone(newconf.get('pattern'), ''))
self.multicore.set(ifNone(newconf.get('multicore'), 0))
self.use_prior.set(ifNone(newconf.get('use_prior'), 0))
self.priorMean.set(ifNone(newconf.get('prior_mean'), 0))
self.priorStdDev.set(ifNone(newconf.get('prior_stdev'), 5))
self.incremental.set(ifNone(newconf.get('incremental'), 0))
self.shuffle.set(ifNone(newconf.get('shuffle'), 0))
self.use_initial_weights.set(ifNone(newconf.get('use_initial_weights'), 0))
self.profile.set(ifNone(newconf.get('profile'), 0))
self.params.set(ifNone(newconf.get('params'), ''))
self.verbose.set(ifNone(newconf.get('verbose'), 1))
self.ignore_unknown_preds.set(ifNone(newconf.get('ignore_unknown_preds'), 0))
self.output_filename.set(ifNone(newconf.get('output_filename'), ''))
self.queryPreds.set(ifNone(newconf.get('qpreds'), ''))
self.evidencePreds.set(ifNone(newconf.get('epreds'), ''))
self.discrPredicates.set(ifNone(newconf.get('discr_preds'), 0))
self.ignore_zero_weight_formulas.set(ifNone(newconf.get('ignore_zero_weight_formulas'), 0))
self.save.set(ifNone(newconf.get('save'), 0))
def parse_db(mln,
content,
ignore_unknown_preds=False,
db=None,
dirs=['.'],
projectpath=None):
'''
Reads one or more databases in a string representation and returns
the respective Database objects.
:param mln: the MLN object which should be used to load the database.
:param content: the string representation of one or multiple ('---'-separated)
databases
:param ignore_unknown_preds: by default this function raises an Exception when it encounters
a predicate in the DB that has not been declared in the associated
MLN. ignore_unknown_preds=True simply ignores such predicates.
:param db: the Database object that shall receive the facts stored in the new DB.
If None, a new `Database` object will be created.
'''
log = logging.getLogger('db')
content = stripComments(content)
allow_multiple = True
if db is None:
allow_multiple = True
db = Database(mln, ignore_unknown_preds=ignore_unknown_preds)
dbs = []
# expand domains with dbtext constants and save evidence
for line, l in enumerate(content.split("\n")):
l = l.strip()
if l == '':
continue
# separator between independent databases
elif l == '---' and not db.isempty():
dbs.append(db)
db = Database(mln)
continue
# domain declaration
elif "{" in l:
domname, constants = db.mln.logic.parse_domain(l)
domnames = [domname for _ in constants]
# include
elif l.startswith('#include'):
filename = l[len("#include "):].strip()
m = re.match(r'"(?P<filename>.+)"', filename)
if m is not None:
filename = m.group('filename')
# if the path is relative, look for the respective file
# relatively to all paths specified. Take the first file matching.
if not mlnpath(filename).exists:
includefilename = None
for d in dirs:
mlnp = '/'.join([d, filename])
if mlnpath(mlnp).exists:
includefilename = mlnp
break
if includefilename is None:
raise Exception('File not found: %s' % filename)
else:
includefilename = filename
else:
m = re.match(r'<(?P<filename>.+)>', filename)
if m is not None:
filename = m.group('filename')
else:
raise MLNParsingError('Malformed #include statement: %s' %
line)
if projectpath is None:
raise MLNParsingError(
'No project specified: Cannot locate import from project: %s'
% filename)
includefilename = ':'.join([projectpath, filename])
logger.debug('Including file: "%s"' % includefilename)
p = mlnpath(includefilename)
dbs.extend(
parse_db(content=mlnpath(includefilename).content,
ignore_unknown_preds=ignore_unknown_preds,
dirs=[p.resolve_path()] + dirs,
projectpath=ifNone(p.project, projectpath,
lambda x: '/'.join(p.path + [x])),
mln=mln))
continue
# valued evidence
elif l[0] in "0123456789":
s = l.find(" ")
gndatom = l[s + 1:].replace(" ", "")
value = float(l[:s])
if value < 0 or value > 1:
raise Exception('Valued evidence must be in [0,1]')
if gndatom in db.evidence:
raise Exception("Duplicate soft evidence for '%s'" % gndatom)
try:
positive, predname, constants = mln.logic.parse_literal(
gndatom
) # TODO Should we allow soft evidence on non-atoms here? (This assumes atoms)
except NoSuchPredicateError, e:
if ignore_unknown_preds: continue
else: raise e
domnames = mln.predicate(predname).argdoms
db << (gndatom, value)
# literal
else:
if l[0] == "?":
raise Exception("Unknown literals not supported (%s)" %
l) # this is an Alchemy feature
try:
true, predname, constants = mln.logic.parse_literal(l)
except NoSuchPredicateError, e:
if ignore_unknown_preds: continue
else: raise e
except Exception, e:
traceback.print_exc()
raise MLNParsingError('Error parsing line %d: %s (%s)' %
(line + 1, l, e.message))
def parse_db(mln, content, ignore_unknown_preds=False, db=None, dirs=['.'], projectpath=None):
'''
Reads one or more databases in a string representation and returns
the respective Database objects.
:param mln: the MLN object which should be used to load the database.
:param content: the string representation of one or multiple ('---'-separated)
databases
:param ignore_unknown_preds: by default this function raises an Exception when it encounters
a predicate in the DB that has not been declared in the associated
MLN. ignore_unknown_preds=True simply ignores such predicates.
:param db: the Database object that shall receive the facts stored in the new DB.
If None, a new `Database` object will be created.
'''
log = logging.getLogger('db')
content = stripComments(content)
allow_multiple = True
if db is None:
allow_multiple = True
db = Database(mln, ignore_unknown_preds=ignore_unknown_preds)
dbs = []
# expand domains with dbtext constants and save evidence
for line, l in enumerate(content.split("\n")):
l = l.strip()
if l == '':
continue
# separator between independent databases
elif l == '---' and not db.isempty():
dbs.append(db)
db = Database(mln)
continue
# domain declaration
elif "{" in l:
domname, constants = db.mln.logic.parse_domain(l)
domnames = [domname for _ in constants]
# include
elif l.startswith('#include'):
filename = l[len("#include "):].strip()
m = re.match(r'"(?P<filename>.+)"', filename)
if m is not None:
filename = m.group('filename')
# if the path is relative, look for the respective file
# relatively to all paths specified. Take the first file matching.
if not mlnpath(filename).exists:
includefilename = None
for d in dirs:
mlnp = '/'.join([d, filename])
if mlnpath(mlnp).exists:
includefilename = mlnp
break
if includefilename is None:
raise Exception('File not found: %s' % filename)
else:
includefilename = filename
else:
m = re.match(r'<(?P<filename>.+)>', filename)
if m is not None:
filename = m.group('filename')
else:
raise MLNParsingError('Malformed #include statement: %s' % line)
if projectpath is None:
raise MLNParsingError('No project specified: Cannot locate import from project: %s' % filename)
includefilename = ':'.join([projectpath, filename])
logger.debug('Including file: "%s"' % includefilename)
p = mlnpath(includefilename)
dbs.extend(parse_db(content=mlnpath(includefilename).content, ignore_unknown_preds=ignore_unknown_preds, dirs=[p.resolve_path()]+dirs,
projectpath=ifNone(p.project, projectpath, lambda x: '/'.join(p.path+[x])), mln=mln))
continue
# valued evidence
elif l[0] in "0123456789":
s = l.find(" ")
gndatom = l[s + 1:].replace(" ", "")
value = float(l[:s])
if value < 0 or value > 1:
raise Exception('Valued evidence must be in [0,1]')
if gndatom in db.evidence:
raise Exception("Duplicate soft evidence for '%s'" % gndatom)
try:
positive, predname, constants = mln.logic.parse_literal(gndatom) # TODO Should we allow soft evidence on non-atoms here? (This assumes atoms)
except NoSuchPredicateError, e:
if ignore_unknown_preds: continue
else: raise e
domnames = mln.predicate(predname).argdoms
db << (gndatom, value)
# literal
else:
if l[0] == "?":
raise Exception("Unknown literals not supported (%s)" % l) # this is an Alchemy feature
try:
true, predname, constants = mln.logic.parse_literal(l)
except NoSuchPredicateError, e:
if ignore_unknown_preds: continue
else: raise e
except Exception, e:
traceback.print_exc()
raise MLNParsingError('Error parsing line %d: %s (%s)' % (line+1, l, e.message))
def parse_mln(text,
searchpaths=['.'],
projectpath=None,
logic='FirstOrderLogic',
grammar='PRACGrammar',
mln=None):
'''
Reads an MLN from a stream providing a 'read' method.
'''
dirs = [
os.path.abspath(os.path.expandvars(os.path.expanduser(p)))
for p in searchpaths
]
formulatemplates = []
text = str(text)
if text == "":
raise MLNParsingError(
"No MLN content to construct model from was given; must specify either file/list of files or content string!"
)
# replace some meta-directives in comments
text = re.compile(r'//\s*<group>\s*$', re.MULTILINE).sub("#group", text)
text = re.compile(r'//\s*</group>\s*$', re.MULTILINE).sub("#group.", text)
# remove comments
text = stripComments(text)
if mln is None:
mln = MLN(logic, grammar)
# read lines
mln.hard_formulas = []
templateIdx2GroupIdx = {}
inGroup = False
idxGroup = -1
fixWeightOfNextFormula = False
fuzzy = False
pseudofuzzy = False
uniquevars = None
fixedWeightTemplateIndices = []
lines = text.split("\n")
iLine = 0
while iLine < len(lines):
line = lines[iLine]
iLine += 1
line = line.strip()
try:
if len(line) == 0: continue
# meta directives
if line == "#group":
idxGroup += 1
inGroup = True
continue
elif line == "#group.":
inGroup = False
continue
elif line.startswith("#fixweight"):
fixWeightOfNextFormula = True
continue
elif line.startswith('#fuzzy'):
if not isinstance(mln.logic, FuzzyLogic):
logger.warning(
'Fuzzy declarations are not supported in %s. Treated as a binary predicate.'
% mln.logic.__class__.__name__)
pseudofuzzy = True
else:
fuzzy = True
continue
elif line.startswith("#include"):
filename = line[len("#include "):].strip()
m = re.match(r'"(?P<filename>.+)"', filename)
if m is not None:
filename = m.group('filename')
# if the path is relative, look for the respective file
# relatively to all paths specified. Take the first file matching.
if not mlnpath(filename).exists:
includefilename = None
for d in dirs:
mlnp = '/'.join([d, filename])
if mlnpath(mlnp).exists:
includefilename = mlnp
break
if includefilename is None:
raise Exception('File not found: %s' % filename)
else:
includefilename = filename
else:
m = re.match(r'<(?P<filename>.+)>', filename)
if m is not None:
filename = m.group('filename')
else:
raise MLNParsingError(
'Malformed #include statement: %s' % line)
if projectpath is None:
raise MLNParsingError(
'No project specified: Cannot locate import from project: %s'
% filename)
includefilename = ':'.join([projectpath, filename])
logger.debug('Including file: "%s"' % includefilename)
p = mlnpath(includefilename)
parse_mln(text=mlnpath(includefilename).content,
searchpaths=[p.resolve_path()] + dirs,
projectpath=ifNone(p.project, projectpath,
lambda x: '/'.join(p.path + [x])),
logic=logic,
grammar=grammar,
mln=mln)
continue
elif line.startswith('#unique'):
try:
uniVars = re.search('#unique{(.+)}', line)
uniVars = uniVars.groups()[0]
uniVars = map(str.strip, uniVars.split(','))
uniquevars = uniVars
except:
raise MLNParsingError(
'Malformed #unique expression: "%s"' % line)
continue
elif line.startswith(
"#AdaptiveMLNDependency"
): # declared as "#AdaptiveMLNDependency:pred:domain"; seems to be deprecated
depPredicate, domain = line.split(":")[1:3]
if hasattr(mln, 'AdaptiveDependencyMap'):
if depPredicate in mln.AdaptiveDependencyMap:
mln.AdaptiveDependencyMap[depPredicate].add(domain)
else:
mln.AdaptiveDependencyMap[depPredicate] = set([domain])
else:
mln.AdaptiveDependencyMap = {depPredicate: set([domain])}
continue
# domain decl
if '=' in line:
# try normal domain definition
parse = mln.logic.parse_domain(line)
if parse is not None:
domName, constants = parse
domName = str(domName)
constants = map(str, constants)
if domName in mln.domains:
logger.debug(
"Domain redefinition: Domain '%s' is being updated with values %s."
% (domName, str(constants)))
if domName not in mln.domains:
mln.domains[domName] = []
mln.constant(domName, *constants)
mln.domain_decls.append(line)
continue
# prior probability requirement
if line.startswith("P("):
m = re.match(r"P\((.*?)\)\s*=\s*([\.\de]+)", line)
if m is None:
raise MLNParsingError(
"Prior probability constraint formatted incorrectly: %s"
% line)
mln.prior(f=mln.logic.parse_formula(m.group(1)),
p=float(m.group(2)))
continue
# posterior probability requirement/soft evidence
if line.startswith("R(") or line.startswith("SE("):
m = re.match(r"(?:R|SE)\((.*?)\)\s*=\s*([\.\de]+)", line)
if m is None:
raise MLNParsingError(
"Posterior probability constraint formatted incorrectly: %s"
% line)
mln.posterior(f=mln.logic.parse_formula(m.group(1)),
p=float(m.group(2)))
continue
# variable definition
if re.match(r'(\$\w+)\s*=(.+)', line):
m = re.match(r'(\$\w+)\s*=(.+)', line)
if m is None:
raise MLNParsingError("Variable assigment malformed: %s" %
line)
mln.vars[m.group(1)] = "%s" % m.group(2).strip()
continue
# predicate decl or formula with weight
else:
isHard = False
isPredDecl = False
if line[-1] == '.': # hard (without explicit weight -> determine later)
isHard = True
formula = line[:-1]
else: # with weight
# try predicate declaration
isPredDecl = True
try:
pred = mln.logic.parse_predicate(line)
except Exception, e:
isPredDecl = False
if isPredDecl:
predname = str(pred[0])
argdoms = map(str, pred[1])
softmutex = False
mutex = None
for i, dom in enumerate(argdoms):
if dom[-1] in ('!', '?'):
if mutex is not None:
raise Exception(
'More than one arguments are specified as (soft-)functional'
)
if fuzzy:
raise Exception(
'(Soft-)functional predicates must not be fuzzy.'
)
mutex = i
if dom[-1] == '?': softmutex = True
argdoms = map(lambda x: x.strip('!?'), argdoms)
pred = None
if mutex is not None:
if softmutex:
pred = SoftFunctionalPredicate(
predname, argdoms, mutex)
else:
pred = FunctionalPredicate(predname, argdoms,
mutex)
elif fuzzy:
pred = FuzzyPredicate(predname, argdoms)
fuzzy = False
else:
pred = Predicate(predname, argdoms)
if pseudofuzzy:
mln.fuzzypreds.append(predname)
pseudofuzzy = False
mln.predicate(pred)
continue
else:
# formula (template) with weight or terminated by '.'
if not isHard:
spacepos = line.find(' ')
weight = line[:spacepos]
formula = line[spacepos:].strip()
try:
formula = mln.logic.parse_formula(formula)
if isHard:
weight = HARD # not set until instantiation when other weights are known
idxTemplate = len(formulatemplates)
formulatemplates.append(formula)
fixweight = False
if inGroup:
templateIdx2GroupIdx[idxTemplate] = idxGroup
if fixWeightOfNextFormula == True:
fixWeightOfNextFormula = False
fixweight = True
fixedWeightTemplateIndices.append(idxTemplate)
# expand predicate groups
for variant in formula.expandgrouplits():
mln.formula(variant,
weight=weight,
fixweight=fixweight,
unique_templvars=uniquevars)
if uniquevars:
uniquevars = None
except ParseException, e:
raise MLNParsingError("Error parsing formula '%s'\n" %
formula)
if fuzzy and not isPredDecl:
raise Exception(
'"#fuzzy" decorator not allowed at this place: %s' %
line)
