def sample_motion(self, N, numeric=True, start_margin=0, end_margin=0): r""" Return a sampling of the motion. TODO: Doc, examples """ a, b = self._interval if numeric: if self._sampling_type == 'uniform': return [self.realization(RR(a + (i/Integer(N)) * (b-a)), numeric=True) for i in range(start_margin, N+1-end_margin)] elif self._sampling_type == 'tan': return [self.realization(tan(RR(a + (i/Integer(N)) * (b-a))), numeric=True) for i in range(start_margin, N+1-end_margin)] else: raise exceptions.NotImplementedError('Sampling ' + str(self._sampling_type) + ' is not supported.') else: if self._sampling_type == 'uniform': return [self.realization(a + (i/Integer(N)) * (b-a)) for i in range(start_margin, N+1-end_margin)] elif self._sampling_type == 'tan': return [self.realization(tan(a + (i/Integer(N)) * (b-a))) for i in range(start_margin, N+1-end_margin)] else: raise exceptions.NotImplementedError('Sampling ' + str(self._sampling_type) + ' is not supported.')
def make_ner_file(self, clean_visible_path, ner_xml_path): '''run tagger a child process to get XML output''' if self.template is None: raise exceptions.NotImplementedError(''' Subclasses must specify a class property "template" that provides command string format for running a tagger. It should take %(tagger_root_path)s as the path from the config file, %(clean_visible_path)s as the input XML file, and %(ner_xml_path)s as the output path to create. ''') tagger_config = dict(tagger_root_path=self.config['tagger_root_path'], clean_visible_path=clean_visible_path, ner_xml_path=ner_xml_path) ## get a java_heap_size or default to 1GB tagger_config['java_heap_size'] = self.config.get('java_heap_size', '') cmd = self.template % tagger_config logger.critical(cmd) start_time = time.time() ## make sure we are using as little memory as possible gc.collect() try: self._child = subprocess.Popen(cmd, stderr=subprocess.PIPE, shell=True) except OSError, exc: msg = traceback.format_exc(exc) msg += make_memory_info_msg(clean_visible_path, ner_xml_path) # instead of sys.ext, do proper shutdown #sys.exit(int(self.config['exit_code_on_out_of_memory'])) raise PipelineOutOfMemory(msg)
def type_name(self): """ Returns the type name. https://heycam.github.io/webidl/#dfn-type-name Note that a type name is not necessarily unique. """ raise exceptions.NotImplementedError()
def realization(self, value, numeric=False): r""" Return the realization for given value of the parameter. TODO: Doc, examples """ res = {} if self._par_type == 'symbolic': subs_dict = { self._parameter : value} for v in self._graph.vertices(): if numeric: res[v] = vector([RR(xi.subs(subs_dict)) for xi in self._parametrization[v]]) else: res[v] = vector([xi.subs(subs_dict) for xi in self._parametrization[v]]) return res elif self._par_type == 'rational': h = self._field.hom(value) for v in self._graph.vertices(): if numeric: res[v] = vector([RR(h(xi)) for xi in self._parametrization[v]]) else: res[v] = vector([h(xi) for xi in self._parametrization[v]]) return res else: raise exceptions.NotImplementedError('')
def print_(self, raw=False, defaults_display='include'): """ Print. Arguments: - raw -- see print_conf - defaults_display -- whether to display defaults and how to display them. Permitted values: - include -- display defaults like any other values inline in appropriate section - exclude -- do not show values same as their default - show, extra -- display default values separately """ print "\n=== %s ===" % self.id if defaults_display: defaults_display = defaults_display.lower() if not defaults_display or defaults_display == 'include': defs = {} show_defaults = False elif defaults_display == 'exclude': defs = self.defaults show_defaults = False elif defaults_display in ('show', 'extra'): defs = self.defaults show_defaults = True else: raise exceptions.NotImplementedError( 'print_ does not know how to handle %s' % (defaults_display, )) self.print_conf(self.conf, raw=raw, defaults=defs, show_defaults=show_defaults)
def does_inherit_getter(self): """ Returns True if |self| inherits its getter. https://heycam.github.io/webidl/#dfn-inherit-getter @return bool """ raise exceptions.NotImplementedError()
def type_name(self): """ Returns type name of this type. https://heycam.github.io/webidl/#dfn-type-name @return str """ raise exceptions.NotImplementedError()
def own_members(self): """ Returns dictionary members which do not include inherited Dictionaries' members. @return tuple(DictionaryMember) """ raise exceptions.NotImplementedError()
def get_fields(self): """ Get serializable fields Must be defined in any subclass """ raise exceptions.NotImplementedError()
def operation_groups(self): """ Returns a list of OperationGroup. Each OperationGroup may have an operation or a set of overloaded operations. @return tuple(OperationGroup) """ raise exceptions.NotImplementedError()
def is_custom(self): """ Returns True if this Constructor is defined in the form of [CustomConstructor=(...)] @return bool """ raise exceptions.NotImplementedError()
def named_constructor(self): """ Returns a named constructor, if this interface has it. Otherwise, returns None. @return NamedConstructor? """ raise exceptions.NotImplementedError()
def exposed_interfaces(self): """ Returns a tuple of Interfaces that are exposed to |self|. If |self| is not a global interface, returns an empty tuple. @return tuple(Interface) """ raise exceptions.NotImplementedError()
def operation_groups(self): """ Returns a tuple of OperationGroup. Each OperationGroup has operation(s) defined in this interface and [Unforgeable] operations in ancestors. @return tuple(OperationGroup) """ raise exceptions.NotImplementedError()
def attributes(self): """ Returns a tuple of attributes including [Unforgeable] attributes in ancestors. @return tuple(Attribute) """ raise exceptions.NotImplementedError()
def inherited_interface(self): """ Returns an Interface from which this interface inherits. If this interface does not inherit, returns None. @return Interface? """ raise exceptions.NotImplementedError()
def exposures(self): """ Returns a set of Exposure's that are applicable on an object. https://heycam.github.io/webidl/#Exposed @return tuple(Expsure) """ raise exceptions.NotImplementedError()
def __init__(self, model, num_samples, num_chains=3, betas=None): """ Initializes the sampler with the model. :param model: The model to sample from. :type model: Valid model Class. :param num_samples: The number of samples to generate. .. Note:: Optimal performance (ATLAS,MKL) is achieved if the number of samples equals the \ batchsize. :type num_samples: :param num_chains: The number of Markov chains. :type num_chains: int :param betas: Array of inverse temperatures to sample from, its dimensionality needs to equal the number of \ chains or if None is given the inverse temperatures are initialized linearly from 0.0 to 1.0 \ in 'num_chains' steps. :type betas: int, None """ if not model._fast_PT: raise ex.NotImplementedError("Only more efficient for Binary RBMs") # Check and set the model if not hasattr(model, 'probability_h_given_v'): raise ex.ValueError("The model needs to implement the function probability_h_given_v!") if not hasattr(model, 'probability_v_given_h'): raise ex.ValueError("The model needs to implement the function probability_v_given_h!") if not hasattr(model, 'sample_h'): raise ex.ValueError("The model needs to implement the function sample_h!") if not hasattr(model, 'sample_v'): raise ex.ValueError("The model needs to implement the function sample_v!") if not hasattr(model, 'energy'): raise ex.ValueError("The model needs to implement the function energy!") if not hasattr(model, 'input_dim'): raise ex.ValueError("The model needs to implement the parameter input_dim!") self.model = model # Initialize persistent Markov chains to Gaussian random samples. self.num_samples = num_samples self.chains = model.sample_v(numx.random.randn(num_chains * self.num_samples, model.input_dim) * 0.01) # Sets the beta values self.num_betas = num_chains if betas is None: self.betas = numx.linspace(0.0, 1.0, num_chains).reshape(num_chains, 1) else: self.betas = self.betas.reshape(numx.array(betas).shape[0], 1) if self.betas.shape[0] != num_chains: raise ex.ValueError("The number of betas and Markov chains must be equivalent!") # Repeat betas batchsize times self.betas = numx.tile(self.betas.T, self.num_samples).T.reshape(num_chains * self.num_samples, 1) # Indices of the chains on temperature beta = 1.0 self.select_indices = numx.arange(self.num_betas - 1, self.num_samples * self.num_betas, self.num_betas)
def create_imgs(self, dir_path, sub_dir): # # FULL_DOC # if 1: raise exceptions.NotImplementedError('check this code!') if URL_STRUCTURE == 1: dest_full = os.path.join(settings.MEDIA_ROOT, settings.DIR_FULL_DOC, sub_dir) else: dest_full = os.path.join(settings.MEDIA_ROOT, settings.DIR_FULL_DOC, sub_dir) cmd = ['%s -path %s' % (IMG_CMD, dest_full)] cmd.append('-format jpg') cmd.append('-define jpeg:size=260x200') cmd.append('-thumbnail 200x %s/*.original' % dir_path) p = subprocess.Popen(' '.join(cmd), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, close_fds=True) retcode = p.wait() if retcode: err_msg = p.stderr.read() print '*** Error' self.error_count += 1 print err_msg if 0: #not parse_error(err_msg): Skip analyse for the moment... sys.exit(1) # # BRIEF_DOC # """ mogrify -path BRIEF_DOC/subdir1/subdir2 -format jpg -thumbnail x110 FULL_DOC/subdir1/subdir2/*.jpg """ dest_brief = os.path.join(settings.MEDIA_ROOT, settings.DIR_BRIEF_DOC, sub_dir) cmd = ['%s -path %s' % (IMG_CMD, dest_brief)] cmd.append('-format jpg') cmd.append('-thumbnail x110 %s/*.jpg' % dest_full) p = subprocess.Popen(' '.join(cmd), shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, close_fds=True) retcode = p.wait() if retcode: err_msg = p.stderr.read() print '*** Error' self.error_count += 1 print err_msg if 0: #not parse_error(err_msg): Skip analyse for the moment... sys.exit(1) return
def named_property_handler(self): """ Returns a set of handlers (getter/setter/deleter) for the named property. @return NamedPropertyHandler? """ # TODO: Include anonymous handlers of ancestors. https://crbug.com/695972 raise exceptions.NotImplementedError()
def is_correct(self, question, parameters): """ Whether the answer is correct. Pass the question itself and the parameters, if any. """ raise exceptions.NotImplementedError( "This question type has no correction method.")
def notice(title="notice_time_limit", msg="Test"): plt = platform.system() if plt == "Darwin": os.system( "osascript -e 'display notification \"{}\" with title \"{}\"'". format(msg, title)) else: raise exceptions.NotImplementedError("Not supported OS **yet**")
def _keyphraseConsumption(self, corpus, keyphrases): """Consumes the keyphrases associcated to the documents of a given corpus. Args: corpus: The C{KBCorpus} from which the keyphrases have been extracted. keyphrases: The extracted keyphrases (C{map} of C{list} of C{KBTextualUnit}s associated to a document's name). """ raise exceptions.NotImplementedError()
def get_newsletter_receiver_collections(self): """ Returns a dict of valid receiver collections has to be overriden in the object to return a tuple of querysets return (('all',{}),) {} is used to filter the queryset when evaluating the get_receiver_filtered_queryset function. """ raise exceptions.NotImplementedError( "Override this method in your class!")
def get_date_for_device(device, filename): ''' Retrieves date from file using device dependent algorithm. :param device: name of device that shot the video. :param filename: name of the file. :return: datetime.date object. ''' if device == 'nexus5': return parse_date_nexus5(filename) else: raise exceptions.NotImplementedError('Unknown device: ' + device)
def _candidateClustering(self, document): """Clusters the candidates of a given document. Args: document: The C{KBDocument} from which the candidates must be clustered. Returns: The C{list} of C{KBTextualUnitCluster}s). """ raise exceptions.NotImplementedError()
def _bell(self): '''ring the bell if requested.''' if self.bell_style == 'none': pass elif self.bell_style == 'visible': raise exceptions.NotImplementedError( "Bellstyle visible is not implemented yet.") elif self.bell_style == 'audible': self.console.bell() else: raise ReadlineError("Bellstyle %s unknown." % self.bell_style)
def loadFromR(self, filename): """ Loads object from R data file. Parameters: filename: string string that gives the filename and the location of the file """ raise exceptions.NotImplementedError( "not implemented to load from Rdata file")
def url(self, _external=False): """ The URL where a JSON representation of the document based on MongoCoderMixin_'s encode_mongo_ method can be found. .. warning:: Subclasses of MongoCoderDocument should implement this method. """ raise exceptions.NotImplementedError( "The single-object URL of this document class is not defined.")
def tokenizeSentences(self, text): """Tokenizes a text into sentences. Args: text: The C{string} text to tokenize. Returns: The ordered C{list} of every C{string} sentence of the C{text}. """ raise exceptions.NotImplementedError()