def set_outputfilename(self):
if not hasattr(self, "output_filename") or not hasattr(self, "db_filename") or not hasattr(self, "mln_filename"):
return
mln = self.mln_container.selected_file.get()
db = self.db_container.selected_file.get()
if "" in (mln, db): return
if self.selected_method.get():
method = LearningMethods.clazz(self.selected_method.get())
methodid = LearningMethods.id(method)
filename = config.learnwts_output_filename(mln, methodid.lower(), db)
self.output_filename.set(filename)
def update_config(self):
out('update_config')
self.config = PRACMLNConfig()
self.config['mln'] = self.mln_container.selected_file.get().strip().lstrip('*')
self.config["db"] = self.db_container.selected_file.get().strip().lstrip('*')
self.config["output_filename"] = self.output_filename.get()
self.config["params"] = self.params.get().strip()
self.config["method"] = LearningMethods.id(self.selected_method.get().strip())
self.config["pattern"] = self.pattern.get()
self.config["use_prior"] = int(self.use_prior.get())
self.config["prior_mean"] = self.priorMean.get()
self.config["prior_stdev"] = self.priorStdDev.get()
self.config["incremental"] = int(self.incremental.get())
self.config["shuffle"] = int(self.shuffle.get())
self.config["use_initial_weights"] = int(self.use_initial_weights.get())
self.config["qpreds"] = self.queryPreds.get().strip()
self.config["epreds"] = self.evidencePreds.get().strip()
self.config["discr_preds"] = self.discrPredicates.get()
self.config['logic'] = self.selected_logic.get()
self.config['grammar'] = self.selected_grammar.get()
self.config['multicore'] = self.multicore.get()
self.config['profile'] = self.profile.get()
self.config['verbose'] = self.verbose.get()
self.config['ignore_unknown_preds'] = self.ignore_unknown_preds.get()
self.config['ignore_zero_weight_formulas'] = self.ignore_zero_weight_formulas.get()
self.config['save'] = self.save.get()
self.config["output_filename"] = self.output_filename.get().strip()
self.project.learnconf = PRACMLNConfig()
self.project.learnconf.update(self.config.config.copy())
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 change_discr_preds(self, *args):
methodname = self.selected_method.get()
if methodname:
method = LearningMethods.clazz(methodname)
state = NORMAL if issubclass(method, DiscriminativeLearner) else DISABLED
self.entry_nePreds.configure(state=state if self.discrPredicates.get() == 0 else DISABLED)
self.entryEvidencePreds.configure(state=state if self.discrPredicates.get() == 1 else DISABLED)
self.rbEvidencePreds.configure(state=state)
self.rbQueryPreds.configure(state=state)
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 method(self):
'''
The string identifier of the learning method to use. Defaults to
``'BPLL'``.
'''
return LearningMethods.clazz(self._config.get('method', 'BPLL'))
