NoReturn:\n pass","def set_params(self, *arg):\n pass","def prepare_data(self):","def fill_info ( fill_num ) : \n global _finfos_\n finfo = _finfos_.get ( fill_num , None )\n if finfo : return finfo \n \n try :\n #\n url = fill_url.format ( fill_num )\n _obj = urllib.urlopen ( url )\n finfo = json.load ( _obj )\n \n finfo = finfo if finfo else None \n \n _finfos_ [ fill_num ] = finfo \n return finfo\n \n except:\n return None \n\n return None","def _prepare_params(self, params):\n for key, value in params.items():\n if type(value) is list:\n params[key] = [(6, 0, value)]\n\n return params","def test_reset_params(self):\n\t\t\n\t\tparams = DEFAULT_PARAMS.copy()\n\t\tparams['fit']=PL\n\t\tvalid = self.watcher.valid_params(params)\n\t\tself.assertTrue(valid)\n\t\tparams = self.watcher.normalize_params(params)\n\t\tself.assertEqual(params['fit'], POWER_LAW)\n\t\t\n\t\tparams = DEFAULT_PARAMS.copy()\n\t\tparams['fit']=TPL\n\t\tvalid = self.watcher.valid_params(params)\n\t\tself.assertFalse(valid)\n\t\t\n\t\tparams = DEFAULT_PARAMS.copy()\n\t\tparams['fit']=TPL\n\t\tparams[PL_PACKAGE]=POWERLAW_PACKAGE\n\t\tparams[XMAX]=XMAX_FORCE\n\n\t\tvalid = self.watcher.valid_params(params)\n\t\tself.assertTrue(valid)\n\t\tparams = self.watcher.normalize_params(params)\n\t\tself.assertEqual(params['fit'], TRUNCATED_POWER_LAW)","def _add_setup_param(self, name, fmt, **kwargs):\n self._param_dict.add(name, '', None, fmt,\n startup_param=False,\n direct_access=True,\n visibility=ParameterDictVisibility.READ_ONLY,\n **kwargs)","def _check_params(self):\n pass","def _append_params(name, param_values, dependency, index, sample):\n\n # Fit distribution\n current_params = Fit._fit_distribution(sample, name)\n\n # Create basic fit object\n basic_fit = BasicFit(*current_params, sample)\n\n for i in range(index, len(dependency)):\n # Check if there is a dependency and whether it is the right one\n if dependency[i] is not None and \\\n dependency[i] == dependency[index]:\n # Calculated parameter is appended to param_values\n param_values[i].append(current_params[i])\n return basic_fit","def set_default_values_as_needed(self):\n if self.verbose:\n click.echo('Updating required default values')\n for field in ARGUMENTS_DEFAULT_VALUES:\n if self.__class__.__name__ in ARGUMENTS_DEFAULT_VALUES[field][1]:\n self.data[field] = ARGUMENTS_DEFAULT_VALUES[field][0]","def _set_fill(self, _var_name, _list_index, _operation):\r\n self.command_stack.do(model.structure.SetFill(self._structure, bool(self._fill_var.get())))","def optional_parameters(self):\n return ['seed', 'param_card', 'apmass', 'map', 'mpid', 'mrhod']","def create_initial_parameters(self):\n update_nested_dictionary(\n self.settings,\n {self.highest_lookup: {\n self.highest_sublookup: self.kw\n }})","def fill_missing_source_parameters(self) -> None:\n\n sp_dict = {sp.source: sp for sp in self.source_parameters}\n sp_out = list()\n for source in self.sources:\n if source in sp_dict:\n sp_out.append(sp_dict[source])\n else:\n sp_out.append(SourceParameterFactory(source))\n\n self.source_parameters = sp_out\n return","def _setup_params_and_bounds(self, param_name, vals, bounds):\n vals_processed = self._process_vals(param_name, vals)\n setattr(self, '__'+param_name, vals_processed)\n bounds_processed = self._process_bounds(param_name, bounds)\n setattr(self, '__'+param_name+'_bounds', bounds_processed)","def fill_missing(self) -> None:\n\n self.fill_missing_rows()\n self.fill_missing_source_parameters()\n return","def define_parameters(self):","def overwrite_hyperparams(self):\n try:\n default_hyperparams = self.hyperparams\n for key in default_hyperparams:\n try:\n flag = self.FLAGS[key]\n param_value = flag.value\n if param_value is not None:\n self.hyperparams[key] = param_value\n except:\n pass\n except:\n pass","def update_values(self, to_update):\n for key, value in kwargs.iteritems():\n self.params[key] = value\n # update the possibly dependent parameters\n self.set_filenames()","def good_params():\n from scraper import PARAMS\n params = PARAMS.copy()\n params['Business_Name'] = 'CodeFellows'\n params['City'] = 'Seattle'\n return params","def _update_params(self):\n _load = not self.san_interface.runmode\n params={}\n if ('iosched' in self._updatedattr or _load) and self.iosched<>IoSchedType.default:\n params['iosched']=str(self.iosched)\n if ('readahead' in self._updatedattr or _load) and self.readahead :\n params['readahead']=self.readahead\n if params:\n for pt in self.paths():\n pt.provider.set_dev_params(pt,params)","def onUpdate(self):\n\t\t#fill all the order that satisfied\n\t\tfor x in filter(self.isFilled,self().keys()):\n\t\t\tself[x].fill()","def filled(self, *args, **kwargs):\n out = getcopy(self)\n out.fill(*args, **kwargs)\n return out","def fit_params(self, rfl_meas, geom, *args):\n\n return np.array([])","def set_params(self, params: Dict) -> None:\n self.leak.set_g(params['g_leak'])\n self.nav.set_g(params['g_nav'])\n self.kvhh.set_g(params['g_kvhh'])\n self.kva.set_g(params['g_kva'])\n self.kvsi.set_g(params['g_kvsi'])\n self.cav.set_g(params['g_cav'])\n self.kca.set_g(params['g_kca'])\n self.nap.set_g(params['g_nap'])\n self.kir.set_g(params['g_kir'])\n self.ampar.set_g(params['g_ampar'])\n self.nmdar.set_g(params['g_nmdar'])\n self.gabar.set_g(params['g_gabar'])\n self.tau_ca = params['t_ca']","def expand_params(self):\n \n no_datasets = len(self.traces)\n no_species = self.reaction_matrix.shape[0]\n \n t0_keys = [key for key in self.input_params.keys() if 't0' in key]\n od_keys = [key for key in self.input_params.keys() if 'OD' in key]\n k_keys = [key for key in self.input_params.keys() if 'k' in key]\n c0_keys = [key for key in self.input_params.keys() if 'c0' in key]\n \n enum_keys = list(enumerate(self.input_params.keys()))\n first_t0 = next(i for i,key in enum_keys if 't0' in key)\n first_od = next(i for i,key in enum_keys if 'OD' in key)\n first_k = next(i for i,key in enum_keys if 'k' in key)\n first_c0 = next(i for i,key in enum_keys if 'c0' in key)\n \n t0_params = [self.input_params.pop(k) for k in t0_keys]\n od_params = [self.input_params.pop(k) for k in od_keys]\n k_params = [self.input_params.pop(k) for k in k_keys]\n c0_params = [self.input_params.pop(k) for k in c0_keys]\n \n if len(t0_keys) == 1 and t0_keys[0] == 't0': \n p = t0_params[0]\n new_t0_params = [] \n for d in range(1,no_datasets+1):\n new_p = copy.deepcopy(p)\n new_p.name += str(d)\n new_t0_params.append(new_p)\n t0_params = new_t0_params\n \n if len(od_keys) == 1 and od_keys[0] == 'OD_offset': \n p = od_params[0]\n new_od_params = []\n for d in range(1,no_datasets+1):\n new_p = copy.deepcopy(p)\n new_p.name += str(d)\n new_od_params.append(new_p)\n od_params = new_od_params\n \n # TODO - this is not adequate - what if the first rate parameter \n # isn't k1?\n if len(k_keys) == self.reaction_matrix.sum() and k_keys[0] == 'k1':\n new_k_params = []\n for p in k_params:\n for d in range(1,no_datasets+1):\n new_p = copy.deepcopy(p) \n new_p.name += str(d)\n new_k_params.append(new_p)\n k_params = new_k_params\n \n if len(c0_keys) == no_species and c0_keys[0] == 'c01':\n new_c0_params = []\n for p in c0_params:\n for d in range(1,no_datasets+1):\n new_p = copy.deepcopy(p)\n new_p.name += str(d)\n new_c0_params.append(new_p)\n c0_params = new_c0_params\n \n # as lmfit parameters objects are ordered dictionaries the order\n # that we do this actually matters and will influence the fitting\n # we would like to allow the used to specify the order and respect the \n # order they choose.\n \n # NB The ideal order is to have the parameters whos initial values are \n # better optimised after the parameters whos initial values are worse \n \n expanded_params = sorted([(t0_params,first_t0),\n (od_params,first_od),\n (k_params,first_k),\n (c0_params,first_c0)], key=lambda e:e[1])\n expanded_params, loc = zip(*expanded_params)\n \n for ep in expanded_params:\n self.input_params.add_many(*ep)","def _reset_parameters(self) -> None:\n self._setup_input = {\n \"P\": csc_matrix(2.0 * self.opt.P(self.p).toarray()),\n \"q\": self.opt.q(self.p).toarray().flatten(),\n }\n if self.opt_type in CONSTRAINED_OPT:\n A = self.opt.A(self.p)\n b = self.opt.b(self.p)\n self._setup_input[\"A\"] = csc_matrix(\n cs.vertcat(self.opt.M(self.p), A, -A).toarray()\n )\n self._setup_input[\"l\"] = (\n cs.vertcat(-self.opt.c(self.p), -b, b).toarray().flatten()\n )","def set_params_BS(self):\n params = self.ctx.input_params_KKR\n\n # maybe overwrite some inputs\n if 'params_kkr_overwrite' in self.inputs:\n self.report(f'found params_kkr_overwrite: {self.inputs.params_kkr_overwrite.get_dict()}')\n updatenode = self.inputs.params_kkr_overwrite\n updatenode.label = 'params overwrite'\n params = update_params_wf(params, updatenode)\n\n input_dict = params.get_dict()\n para_check = kkrparams()\n try:\n for key, val in input_dict.items():\n para_check.set_value(key, val, silent=True)\n except:\n return self.exit_codes.ERROR_CALC_PARAMETERS_INVALID # pylint: disable=no-member\n label = ''\n descr = f'(pk - {self.inputs.remote_data.pk}, and uuid - {self.inputs.remote_data.uuid})'\n\n missing_list = para_check.get_missing_keys(use_aiida=True)\n\n if missing_list != []:\n kkrdefaults = kkrparams.get_KKRcalc_parameter_defaults()[0]\n kkrdefaults_updated = []\n for key_default, val_default in list(kkrdefaults.items()):\n if key_default in missing_list:\n para_check.set_value(key_default, val_default)\n kkrdefaults_updated.append(key_default)\n missing_list.remove(key_default)\n if len(missing_list) > 0:\n self.report(f'ERROR: calc_parameters misses keys: {missing_list}')\n return self.exit_codes.ERROR_CALC_PARAMETERS_INCOMPLETE # pylint: disable=no-member\n else:\n self.report(f'updated KKR parameter node with default values: {kkrdefaults_updated}')\n label = 'add_defaults_'\n descr = 'added missing default keys, '\n ##+++ Starts to add the NTP2, EMAX and EMIN from the\n econt_new = self.ctx.BS_params_dict\n if self.ctx.struc_is_alloy:\n if econt_new.get('kmesh', None) is None:\n econt_new['kmesh'] = [1, 1, 1] # overwrite kmesh since the kpoints are used from the input\n kkr_calc = self.inputs.remote_data.get_incoming(node_class=KkrCalculation).first().node\n ef = kkr_calc.outputs.output_parameters.get_dict()['fermi_energy'] # unit in Ry\n self.ctx.fermi_energy = ef ## in Ry unit\n\n # Set BS params\n try:\n para_check = set_energy_params(econt_new, ef, para_check)\n except:\n return self.exit_codes.ERROR_CALC_PARAMETERS_INVALID # pylint: disable=no-member\n\n para_check.set_multiple_values(\n NPT1=0,\n NPT3=0,\n NPOL=0,\n )\n\n updatenode = Dict(para_check.get_dict())\n updatenode.label = label + 'KKRparam_BS'\n updatenode.description = 'KKR parameter node extracted from remote_folder' + descr + ' as well as wf_parameter input node.'\n\n paranode_BS = update_params_wf(self.ctx.input_params_KKR, updatenode)\n self.ctx.BS_kkrparams = paranode_BS","def addParameters(self):\n\n self.pRefArray = self.addParam(\"ikrefarray\", \"string\", \"\")\n self.pUseIndex = self.addParam(\"useIndex\", \"bool\", False)\n\n self.pParentJointIndex = self.addParam(\n \"parentJointIndex\", \"long\", -1, None, None)\n\n self.pJoint = self.addParam(\"joint\", \"bool\", True)","def set_params(self, params):\n for step_id, step_params in _iteritems(params):\n for name, value in _iteritems(step_params):\n self.add_param(step_id, name, value)","def _fillData(self, extras):\n e = {k : (\" \".join(v[\"words\"])\n if type(v) == dict and \"words\" in v else v) for k, v in extras.items()}\n return self.data % e","def fill_item(self, args, producing_job):\n pass","def set_params(self, params: Dict) -> None:\n self.leak.set_g(params[\"g_leak\"])\n self.kvhh.set_g(params[\"g_kvhh\"])\n self.cav.set_g(params[\"g_cav\"])\n self.kca.set_g(params[\"g_kca\"])\n self.nap.set_g(params[\"g_nap\"])\n self.tau_ca = params[\"t_ca\"]","def set_params(self, dic):\n if dic is not None:\n for key, val in zip(dic.keys(), dic.values()):\n if key in self.__dict__.keys():\n self.__dict__[key] = val\n\n if 'scale_params' in self.__dict__.keys():\n self.scale_params.set_params(dic)\n if 'atmospheric_params' in self.__dict__.keys():\n if self.atmospheric_params is not None:\n self.atmospheric_params.set_params(dic)\n\n if 'atemperature_params' in self.__dict__.keys():\n if self.atemperature_params is not None:\n self.atemperature_params.set_params(dic)\n\n if 'oceanic_params' in self.__dict__.keys():\n if self.oceanic_params is not None:\n self.oceanic_params.set_params(dic)\n\n if 'ground_params' in self.__dict__.keys():\n if self.ground_params is not None:\n self.ground_params.set_params(dic)\n\n if 'otemperature_params' in self.__dict__.keys():\n if self.gotemperature_params is not None:\n self.gotemperature_params.set_params(dic)\n\n if 'gtemperature_params' in self.__dict__.keys():\n if self.gotemperature_params is not None:\n self.gotemperature_params.set_params(dic)","def add_data(self,**kwargs):\n self.given_data.update([x for x in kwargs.keys() if kwargs[x]!=None ])\n for i in range(len(self.attr)):\n param=self.attr[i]\n if param in kwargs and kwargs[param]!=None:\n if i==0 and not (0 <= kwargs['angle'] <= 90) :# atribute is angle\n raise ValueError('Angle should be between 0 an 90 degrees')\n elif i==7 and not (0 <= kwargs[param] <= 1):\n raise ValueError('Coefficient (kf) should be between 0 and 1')\n else:\n self.data[param]=kwargs[param]\n print('Added data to object. See current data by using print(object_name) or using check_data method')","def set_parameters(self, full=None, r=None, l=None, d=None, z=None):\n\n original = _deepcopy(self.parameters) # save in case of error\n\n if type(full) is bool:\n self.parameters[\"full\"] = full\n if type(r) in [int, float]:\n self.parameters[\"r\"] = float(r)\n if self._type == 2: # observation well\n if type(d) in [int, float]:\n self.parameters[\"d\"] = float(d)\n if type(l) in [int, float]:\n self.parameters[\"l\"] = float(l)\n else: # piezometer\n if type(z) in [int, float]:\n self.parameters[\"z\"] = float(z)\n\n flag, message = self.validate_parameters()\n if not flag:\n print(message)\n self.parameters.update(original)\n # End Function","def _populate_default_values(self):\n\n if 'input_data' not in self._definition:\n self._definition['input_data'] = []\n for input_dict in self._definition['input_data']:\n if 'required' not in input_dict:\n input_dict['required'] = True\n\n if 'jobs' not in self._definition:\n self._definition['jobs'] = []\n for job_dict in self._definition['jobs']:\n if 'recipe_inputs' not in job_dict:\n job_dict['recipe_inputs'] = []\n if 'dependencies' not in job_dict:\n job_dict['dependencies'] = []\n for dependency_dict in job_dict['dependencies']:\n if 'connections' not in dependency_dict:\n dependency_dict['connections'] = []","def __prepare_dh_params(self):\n self.alpha = symbols('alpha0:' + str(self.joint_count))\n self.a = symbols('a0:' + str(self.joint_count))\n self.q = symbols('q1:' + str(self.joint_count + 1))\n self.d = symbols('d1:' + str(self.joint_count + 1))","def set_params(self, *, params: Params) -> None: # pragma: no cover\n\t\tsuper().set_params(params=params)","def monkey_set_f_params(self):\n self._monkey_set_f_params_counter += 1","def monkey_set_f_params(self):\n self._monkey_set_f_params_counter += 1","def get_complete_parameters(self, auth_request_params):\n params = super().get_complete_parameters(auth_request_params)\n params.update(\n {\n \"id_token\": sign_id_token(self.get_apple_id_token_payload()),\n \"user\": json.dumps(\n {\n \"email\": \"private@appleid.apple.com\",\n \"name\": {\n \"firstName\": \"A\",\n \"lastName\": \"B\",\n },\n }\n ),\n }\n )\n return params","def _autoInitPars(self):\n for p in self._pars:\n setattr(self,p,self.defaultparval)","def set_params(self, **params):\n if('threshold' in params.keys()):\n self.threshold = params['threshold']\n if('subsample' in params.keys()):\n self.subsample = params['subsample']\n if('estimator' in params.keys()):\n self.estimator = params['estimator']\n if('n_folds' in params.keys()):\n self.n_folds = params['n_folds']\n if('stratify' in params.keys()):\n self.stratify = params['stratify']\n if('random_state' in params.keys()):\n self.random_state = params['random_state']\n if('n_jobs' in params.keys()):\n self.n_jobs = params['n_jobs']","def params(self,new):\n self._params = new\n self._config_set()\n self._make_model()","def add_params(self, params):\n return self.set_param('params', params)","def set_scan_params(self, session, params):\n if params['reset']:\n self._set_default_scan_params()\n for k in ['az_speed', 'az_accel']:\n if params[k] is not None:\n self.scan_params[k] = params[k]\n self.log.info('Updated default scan params to {sp}', sp=self.scan_params)\n yield\n return True, 'Done'","def apply_filling(data, filling_list):\n method_name = filling_list[0][MethodKeys.METHOD]\n method_params = filling_list[0][MethodKeys.PARAMETERS]\n return NonSeqFillingMethods.get_method(method_name)(**method_params)(\n data)","def _register_global_params(self, params):\n\n for name,obj in self.params().items():\n global_params.add(**{name:obj})\n\n for name,val in params.items():\n global_params.params(name).default=val\n\n params.update(global_params.get_param_values())\n params[\"name\"]=self.name","def set_params(self, **kargs):\n\n # may further modify parameters manually\n if len(kargs) > 0:\n for key in kargs:\n if key in self.params[self.profile].keys():\n self.params[self.profile][key] = kargs[key]\n else:\n print '%s not a standard key. Will not be used.' % (key)\n \n self.pathout = self.params[self.profile]['pathout']\n self.chans = self.params[self.profile]['chans']\n self.dmarr = self.params[self.profile]['dmarr']\n self.pulsewidth = self.params[self.profile]['pulsewidth'] * n.ones(len(self.chans))\n self.approxuvw = self.params[self.profile]['approxuvw']\n self.beam_params = self.params[self.profile]['beam_params']\n self.long = self.params[self.profile]['long']\n self.lat = self.params[self.profile]['lat']","def _fill_experiment_parameters(self, prediction_type: str, prediction_column: str, holdout_size: float,\n csv_separator: str = ',', excel_sheet: Union[str, int] = 0,\n encoding: str = 'utf-8') -> None:\n self.auto_pipeline_params = {\n 'prediction_type': prediction_type,\n 'prediction_column': prediction_column,\n 'holdout_size': holdout_size,\n 'csv_separator': csv_separator,\n 'excel_sheet': excel_sheet,\n 'encoding': encoding\n }","def update_parameters(self,like_params):\n\n # get current dictionary with parameters, update and setup again\n params=self.get_params()\n\n for par in like_params:\n if par.name in params:\n params[par.name]=par.value\n\n self._setup_from_parameters(params)\n return","def fill_args(cls, toolchain, parser):\n pass # pass must be overloaded (if required)","def _populate_params(self):\n self.params = []\n for root, dirs, files in os.walk(os.curdir):\n for file in files:\n fullfile = str(os.path.join(root, file))\n if self.config.regex_find_params.match(fullfile):\n self.params.append(fullfile)","def check_data(self):\n\n missing_params = {}\n flag = False\n\n missing_params['general'] = {}\n for name, param in self.params.items():\n if not param.check():\n missing_params['general'][name] = param.get_description()\n flag = True\n\n for component, comp_obj in self.components.items():\n missing_params[component], flag_comp = comp_obj.check_data()\n\n # Assign empty component parameters that have a general version:\n empty_general_params = set(missing_params[component]).intersection(\n set(self.params))\n for param in empty_general_params:\n comp_obj.change_param_object(param, self.params[param])\n del missing_params[component][param]\n\n if missing_params[component]:\n flag = True\n\n if flag:\n raise Exception('Following parameters are missing:\\n{}'\n .format(\n self._print_params(missing_params, disp=False)))\n\n return True"],"string":"[\n \"def fill_missing_parameters(self):\\n pseudo_id = self.get_param_by_type(PseudoID)\\n pseudo_name = self.get_param_by_type(PseudoName)\\n if pseudo_id is None and pseudo_name is not None:\\n self.parameters.append(\\n PseudoID(pseudo_name.value)\\n ) # take name for both\\n elif pseudo_name is None and pseudo_id is not None:\\n self.parameters.append(\\n PseudoName(pseudo_id.value)\\n ) # take id for both\",\n \"def _assign_fields_to_params(cls, fields, params):\\n if fields is None:\\n fields = cls.get_default_read_fields()\\n if fields:\\n params['fields'] = ','.join(fields)\",\n \"def _update_params(self):\\n pass\",\n \"def fill_values(self, values=None):\\n if values is None:\\n return\\n\\n info = {}\\n if not self.params:\\n info.update(values)\\n for param in self.params:\\n if param in values:\\n info[param] = values[param]\\n self.hash_info = HashInfo(\\n self.PARAM_PARAMS,\\n info, # type: ignore[arg-type]\\n )\",\n \"def _setup_params(self,**params):\\n ### a parameter might be passed in for one of the extra_pos;\\n ### if a key in the params dict is not a *parameter* of this\\n ### PO, then try it on the extra_pos\\n for n,p in params.items():\\n if n not in self.params():\\n self.set_parameter_value(n,p)\\n del params[n]\\n\\n Parameterized._setup_params(self,**params)\",\n \"def set_params(self, params_):\\n x_start, x_end = params_[\\\"lim_fit\\\"]\\n self.find_idx_of_fit_limit(x_start, x_end)\\n self.is_error_bar_for_fit = params_[\\\"use_error_bar\\\"]\\n self.fitting_method1 = params_[\\\"method1\\\"]\\n self.fitting_method2 = params_[\\\"method2\\\"]\\n self.qty_to_min = params_[\\\"qty_to_min\\\"]\\n\\n for i, key in enumerate(self.params):\\n # self.params[key].set(value=params_[\\\"val\\\"][i], min=params_[\\\"min\\\"][i], max=params_[\\\"max\\\"][i], vary=bool(params_[\\\"hold\\\"][i]), brute_step=params_[\\\"brute_step\\\"][i])\\n if self.params[key].user_data is not None:\\n if \\\"dontGenerate\\\" in self.params[key].user_data:\\n continue\\n self.params[key].set(value=params_[key][\\\"value\\\"], min=params_[key][\\\"min\\\"], max=params_[key][\\\"max\\\"], vary=params_[key][\\\"vary\\\"], brute_step=params_[key][\\\"b_step\\\"])\",\n \"def update_params(self):\\n pass\",\n \"def _apply_params(self):\\n config = self.get_startup_config()\\n # Pass true to _set_params so we know these are startup values\\n self._set_params(config, True)\",\n \"def _inject_params(self, params):\\n\\n params.extend([DomainParam(), InputTemplateFileParam(),\\n OutputDirectoryParam(), LocaleParam(),\\n WidthParam(), NoWrapParam(), OutputFileParam()])\\n\\n return super()._inject_params(params)\",\n \"def set_params(self):\\r\\n pass\",\n \"def gather_params(self):\\n for layer in self.layers:\\n for name, value in layer.params.iteritems():\\n self.params[name] = value\",\n \"def init_params(self):\\n blah\",\n \"def add_default_params(self, params):\\n params['key'] = self.key\\n params['format'] = self.format\\n #params['unique_id'] = generate_unique_id()\\n return params\",\n \"def _validate_params(self):\\n assert set(self.required_params) - set(self._params) == set()\\n for par, val in self.optional_params.items():\\n if par not in self._params:\\n self._params[par] = val\",\n \"def _inject_params(self, params):\\n\\n params.extend([LocaleParam(), CompileDomainsParam(),\\n UseFuzzyParam(), StatisticsParam(),\\n DirectoryParam(), OutputFileParam()])\\n\\n return super()._inject_params(params)\",\n \"def fill_fitarg(self, **kwargs):\\n # set the fit arguments\\n fitarg = {}\\n #fitarg.update(kwargs['pinit'])\\n #for k in kwargs['limits'].keys():\\n # fitarg['limit_{0:s}'.format(k)] = kwargs['limits'][k]\\n # fitarg['fix_{0:s}'.format(k)] = kwargs['fix'][k]\\n # fitarg['error_{0:s}'.format(k)] = kwargs['pinit'][k] * kwargs['int_steps']\\n#\\n# fitarg = OrderedDict(sorted(fitarg.items()))\\n fitarg['pinit'] = kwargs['pinit']\\n fitarg['limits'] = kwargs['limits']\\n fitarg['fix'] = kwargs['fix']\\n fitarg['error'] = OrderedDict()\\n\\n for k in kwargs['limits'].keys():\\n fitarg['error'][k] = kwargs['pinit'][k] * kwargs['int_steps']\\n\\n # get the names of the parameters\\n self._par_names = list(kwargs['pinit'].keys())\\n self._par_islog = kwargs['islog']\\n return fitarg\",\n \"def auto_populate_parameters(self):\\n run_arguments = get_func_arguments(self.run)\\n\\n if not run_arguments:\\n return\\n\\n # ignore 'self' argument, should be safe-ish\\n if \\\"self\\\" in list(run_arguments.keys()):\\n run_arguments.pop(\\\"self\\\")\\n\\n for param_name, default_value in run_arguments.items():\\n is_required = default_value == RequiresValueType\\n if is_required:\\n run_arguments[param_name] = str() # fill to make sure every argument has something\\n\\n if run_arguments:\\n self.param_grid.from_data(run_arguments)\\n self._parameters_auto_generated = True\",\n \"def enrich_params(self):\\n\\n self.params['nmaps'] = len(self.params['probes']) + np.sum(self.params['spins'] == 2)\\n\\n pass\",\n \"def set_params(self, params):\",\n \"def _build_update_params(self, params):\",\n \"def fill_order_info(self, fill_order_info):\\n\\n self._fill_order_info = fill_order_info\",\n \"def _populate(self):\\n self.addDemographics()\\n self.addLabs()\\n self.addProblems()\\n self.addMeds()\\n self.addAllergies()\\n self.addImmunizations()\\n self.addVitals()\\n self.populated_p = True\",\n \"def setupParameters(self, **pars):\\n \\n seldict = {}\\n for k,v in pars.items():\\n if v != None and v != \\\"\\\":\\n seldict[k] = v\\n \\n return seldict\",\n \"def init_params(self):\\n self.clear()\\n self._init_load_data()\\n self._init_net_delay_data()\",\n \"def _update_params(self):\\n raise NotImplementedException()\",\n \"def initialize_params(self, params):\\n pass\",\n \"def set_params(self, **kwargs):\\n ...\",\n \"def initializeParameters(self):\\n\\n self.params[2].value = False\\n self.params[3].enabled = False\\n self.params[7].value = True\\n self.params[7].enabled = False\\n self.params[8].value = None\\n self.params[8].enabled = False\",\n \"def set_packed(self, params):\\n self._params = params\",\n \"def fill(self, **kwargs):\\r\\n for name in kwargs.keys():\\r\\n setattr(self, name, kwargs[name])\\r\\n return self\",\n \"def _update_params(self, perf_params, loop_info):\\n for vartype in list(perf_params.keys()):\\n for var in perf_params[vartype]:\\n self.tspec_params['performance_params'][var] = \\\\\\n self.indent + 'param %s[] = %s;\\\\t#%s\\\\n' % (var, repr(default_perf_params[vartype]), vartype)\\n\\n #loop_info.vars: set of input vars\",\n \"def _initialize_defaults(self):\\n for key, value in defaults.items():\\n if key not in self.source_params:\\n self.source_params[key] = value\",\n \"def _initialize_defaults(self):\\n for key, value in defaults.items():\\n if key not in self.source_params:\\n self.source_params[key] = value\",\n \"def fill_data_parameters(params):\\n # These data paths are created according to our data storage format, and should be adjusted\\n # accordingly.\\n params_data = params.data\\n params_data['subj_data_fname_data_array'] = os.path.join(\\n params_data['data_dir'],\\n params_data['subject_id'],\\n params_data['subject_id'] + '_' + params_data['proc_slug'] + '_data_array.npz')\\n\\n params_data['subj_data_fname_response_array'] = os.path.join(\\n params_data['data_dir'],\\n params_data['subject_id'],\\n params_data['subject_id'] + '_' + params_data['proc_slug'] + '_response_array.npz')\\n\\n params_data['subj_data_fname_response_time_array'] = os.path.join(\\n params_data['data_dir'],\\n params_data['subject_id'],\\n params_data['subject_id'] + '_' +\\n params_data['proc_slug'] + '_response_time_array.npz')\\n\\n params_data['subj_data_fname_question_array'] = os.path.join(\\n params_data['data_dir'],\\n params_data['subject_id'],\\n params_data['subject_id'] + '_' +\\n params_data['proc_slug'] + '_question_array.npz')\\n\\n params_data['subj_data_fname_all'] = os.path.join(\\n params_data['data_dir'],\\n params_data['subject_id'],\\n params_data['subject_id'] + '_' +\\n params_data['proc_slug'] + '.npz')\\n\\n params['latest_data_path'] = os.path.join(params['output']['path_outputs'], 'latest_data.pkl')\\n\\n return params\",\n \"def update_start_values(self, params):\\n allparwids = {}\\n for comp in self.fit_components.values():\\n if comp.usebox is not None and comp.usebox.IsChecked():\\n for name, parwids in comp.parwids.items():\\n allparwids[name] = parwids\\n\\n for pname, par in params.items():\\n if pname in allparwids:\\n allparwids[pname].value.SetValue(par.value)\",\n \"def set_params(self, **params):\\n return super().set_params(**params)\",\n \"def _update(self):\\n self.all_params = {}\\n self._update_experiment_params()\\n self._update_preprocessing_params()\\n self._update_model_params()\",\n \"def set_params(self):\\n raise NotImplementedError\",\n \"def set_params(self, **params):\\n\\n return super().set_params(**params)\",\n \"def append_basic_fit(self, param ,basic_fit):\\n if param == SHAPE_STRING:\\n self._shape_value[0].append(basic_fit.shape)\\n self._shape_value[1].append(basic_fit.loc)\\n self._shape_value[2].append(basic_fit.scale)\\n self.shape_samples.append(basic_fit.samples)\\n elif param == LOCATION_STRING:\\n self._loc_value[0].append(basic_fit.shape)\\n self._loc_value[1].append(basic_fit.loc)\\n self._loc_value[2].append(basic_fit.scale)\\n self.loc_samples.append(basic_fit.samples)\\n elif param == SCALE_STRING:\\n self._scale_value[0].append(basic_fit.shape)\\n self._scale_value[1].append(basic_fit.loc)\\n self._scale_value[2].append(basic_fit.scale)\\n self.scale_samples.append(basic_fit.samples)\\n else:\\n err_msg = \\\"Parameter '{}' is unknown.\\\".format(param)\\n raise ValueError(err_msg)\",\n \"def set_params(self, params):\\n for item in params:\\n if len(item.split(\\\"-\\\")) == 5:\\n self.params[item.split(\\\"-\\\")[-1]] = params[item]\\n elif item.split(\\\"-\\\")[4] == \\\"BECKE88\\\":\\n self.becke88.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"BECKE88_LR\\\":\\n self.becke88_lr.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"BECKE88_LR_ADIABATIC\\\":\\n self.becke88_lr_adiabatic.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"BECKE97\\\":\\n self.becke97.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"BECKE_ROUSSEL\\\":\\n self.becke_roussel.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"BEEF\\\":\\n self.beef.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"CS1\\\":\\n self.cs1.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"GV09\\\":\\n self.gv09.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"HCTH\\\":\\n self.hcth.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"KE_GGA\\\":\\n self.ke_gga.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"KE_LIBXC\\\":\\n self.ke_libxc.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"LDA_HOLE_T_C_LR\\\":\\n self.lda_hole_t_c_lr.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"LIBXC\\\":\\n self.libxc.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"LYP\\\":\\n self.lyp.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"LYP_ADIABATIC\\\":\\n self.lyp_adiabatic.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"OPTX\\\":\\n self.optx.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"P86C\\\":\\n self.p86c.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"PADE\\\":\\n self.pade.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"PBE\\\":\\n self.pbe.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"PBE_HOLE_T_C_LR\\\":\\n self.pbe_hole_t_c_lr.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"PW92\\\":\\n self.pw92.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"PZ81\\\":\\n self.pz81.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"TF\\\":\\n self.tf.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"TFW\\\":\\n self.tfw.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"TPSS\\\":\\n self.tpss.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"VWN\\\":\\n self.vwn.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"XALPHA\\\":\\n self.xalpha.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"XGGA\\\":\\n self.xgga.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[4] == \\\"XWPBE\\\":\\n self.xwpbe.set_params({item: params[item]})\\n else:\\n pass\",\n \"def fill_learner_params(params, inputs, targets, num_question_features=None,\\n num_word_features=None):\\n params_learn = params.learning\\n if params_learn['model'] == RidgeWithLearnedAttention:\\n params_learn['model_params']['num_outputs'] = [targets.shape[-1]]\\n params_learn['model_params']['num_word_features'] = [num_word_features]\\n params_learn['model_params']['num_question_features'] = [num_question_features]\",\n \"def update_params(self, extra_params):\\n self._params.update(extra_params)\\n return self\",\n \"def _set_params(self, params, defaults):\\n new_params = OrderedDict(\\n zip(params, [x if isinstance(x, Parameter) else Parameter() for x in defaults])\\n )\\n for key, value in self._src.items():\\n if key in new_params:\\n new_params[key] = value\\n\\n self._src = new_params\",\n \"def addParams(self, *params):\\n for param in params:\\n self.addParam(param)\\n self.params = list(set(self.params))\",\n \"def set_params(self, params):\\n for item in params:\\n if len(item.split(\\\"-\\\")) == 6:\\n self.params[item.split(\\\"-\\\")[-1]] = params[item]\\n elif item.split(\\\"-\\\")[5] == \\\"BECKE88\\\":\\n self.becke88.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"BECKE88_LR\\\":\\n self.becke88_lr.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"BECKE88_LR_ADIABATIC\\\":\\n self.becke88_lr_adiabatic.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"BECKE97\\\":\\n self.becke97.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"BECKE_ROUSSEL\\\":\\n self.becke_roussel.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"BEEF\\\":\\n self.beef.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"CS1\\\":\\n self.cs1.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"GV09\\\":\\n self.gv09.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"HCTH\\\":\\n self.hcth.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"KE_GGA\\\":\\n self.ke_gga.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"KE_LIBXC\\\":\\n self.ke_libxc.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"LDA_HOLE_T_C_LR\\\":\\n self.lda_hole_t_c_lr.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"LIBXC\\\":\\n self.libxc.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"LYP\\\":\\n self.lyp.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"LYP_ADIABATIC\\\":\\n self.lyp_adiabatic.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"OPTX\\\":\\n self.optx.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"P86C\\\":\\n self.p86c.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"PADE\\\":\\n self.pade.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"PBE\\\":\\n self.pbe.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"PBE_HOLE_T_C_LR\\\":\\n self.pbe_hole_t_c_lr.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"PW92\\\":\\n self.pw92.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"PZ81\\\":\\n self.pz81.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"TF\\\":\\n self.tf.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"TFW\\\":\\n self.tfw.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"TPSS\\\":\\n self.tpss.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"VWN\\\":\\n self.vwn.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"XALPHA\\\":\\n self.xalpha.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"XGGA\\\":\\n self.xgga.set_params({item: params[item]})\\n elif item.split(\\\"-\\\")[5] == \\\"XWPBE\\\":\\n self.xwpbe.set_params({item: params[item]})\\n else:\\n pass\",\n \"def set_params(self, **kwargs) -> NoReturn:\\n pass\",\n \"def set_params(self, *arg):\\n pass\",\n \"def prepare_data(self):\",\n \"def fill_info ( fill_num ) : \\n global _finfos_\\n finfo = _finfos_.get ( fill_num , None )\\n if finfo : return finfo \\n \\n try :\\n #\\n url = fill_url.format ( fill_num )\\n _obj = urllib.urlopen ( url )\\n finfo = json.load ( _obj )\\n \\n finfo = finfo if finfo else None \\n \\n _finfos_ [ fill_num ] = finfo \\n return finfo\\n \\n except:\\n return None \\n\\n return None\",\n \"def _prepare_params(self, params):\\n for key, value in params.items():\\n if type(value) is list:\\n params[key] = [(6, 0, value)]\\n\\n return params\",\n \"def test_reset_params(self):\\n\\t\\t\\n\\t\\tparams = DEFAULT_PARAMS.copy()\\n\\t\\tparams['fit']=PL\\n\\t\\tvalid = self.watcher.valid_params(params)\\n\\t\\tself.assertTrue(valid)\\n\\t\\tparams = self.watcher.normalize_params(params)\\n\\t\\tself.assertEqual(params['fit'], POWER_LAW)\\n\\t\\t\\n\\t\\tparams = DEFAULT_PARAMS.copy()\\n\\t\\tparams['fit']=TPL\\n\\t\\tvalid = self.watcher.valid_params(params)\\n\\t\\tself.assertFalse(valid)\\n\\t\\t\\n\\t\\tparams = DEFAULT_PARAMS.copy()\\n\\t\\tparams['fit']=TPL\\n\\t\\tparams[PL_PACKAGE]=POWERLAW_PACKAGE\\n\\t\\tparams[XMAX]=XMAX_FORCE\\n\\n\\t\\tvalid = self.watcher.valid_params(params)\\n\\t\\tself.assertTrue(valid)\\n\\t\\tparams = self.watcher.normalize_params(params)\\n\\t\\tself.assertEqual(params['fit'], TRUNCATED_POWER_LAW)\",\n \"def _add_setup_param(self, name, fmt, **kwargs):\\n self._param_dict.add(name, '', None, fmt,\\n startup_param=False,\\n direct_access=True,\\n visibility=ParameterDictVisibility.READ_ONLY,\\n **kwargs)\",\n \"def _check_params(self):\\n pass\",\n \"def _append_params(name, param_values, dependency, index, sample):\\n\\n # Fit distribution\\n current_params = Fit._fit_distribution(sample, name)\\n\\n # Create basic fit object\\n basic_fit = BasicFit(*current_params, sample)\\n\\n for i in range(index, len(dependency)):\\n # Check if there is a dependency and whether it is the right one\\n if dependency[i] is not None and \\\\\\n dependency[i] == dependency[index]:\\n # Calculated parameter is appended to param_values\\n param_values[i].append(current_params[i])\\n return basic_fit\",\n \"def set_default_values_as_needed(self):\\n if self.verbose:\\n click.echo('Updating required default values')\\n for field in ARGUMENTS_DEFAULT_VALUES:\\n if self.__class__.__name__ in ARGUMENTS_DEFAULT_VALUES[field][1]:\\n self.data[field] = ARGUMENTS_DEFAULT_VALUES[field][0]\",\n \"def _set_fill(self, _var_name, _list_index, _operation):\\r\\n self.command_stack.do(model.structure.SetFill(self._structure, bool(self._fill_var.get())))\",\n \"def optional_parameters(self):\\n return ['seed', 'param_card', 'apmass', 'map', 'mpid', 'mrhod']\",\n \"def create_initial_parameters(self):\\n update_nested_dictionary(\\n self.settings,\\n {self.highest_lookup: {\\n self.highest_sublookup: self.kw\\n }})\",\n \"def fill_missing_source_parameters(self) -> None:\\n\\n sp_dict = {sp.source: sp for sp in self.source_parameters}\\n sp_out = list()\\n for source in self.sources:\\n if source in sp_dict:\\n sp_out.append(sp_dict[source])\\n else:\\n sp_out.append(SourceParameterFactory(source))\\n\\n self.source_parameters = sp_out\\n return\",\n \"def _setup_params_and_bounds(self, param_name, vals, bounds):\\n vals_processed = self._process_vals(param_name, vals)\\n setattr(self, '__'+param_name, vals_processed)\\n bounds_processed = self._process_bounds(param_name, bounds)\\n setattr(self, '__'+param_name+'_bounds', bounds_processed)\",\n \"def fill_missing(self) -> None:\\n\\n self.fill_missing_rows()\\n self.fill_missing_source_parameters()\\n return\",\n \"def define_parameters(self):\",\n \"def overwrite_hyperparams(self):\\n try:\\n default_hyperparams = self.hyperparams\\n for key in default_hyperparams:\\n try:\\n flag = self.FLAGS[key]\\n param_value = flag.value\\n if param_value is not None:\\n self.hyperparams[key] = param_value\\n except:\\n pass\\n except:\\n pass\",\n \"def update_values(self, to_update):\\n for key, value in kwargs.iteritems():\\n self.params[key] = value\\n # update the possibly dependent parameters\\n self.set_filenames()\",\n \"def good_params():\\n from scraper import PARAMS\\n params = PARAMS.copy()\\n params['Business_Name'] = 'CodeFellows'\\n params['City'] = 'Seattle'\\n return params\",\n \"def _update_params(self):\\n _load = not self.san_interface.runmode\\n params={}\\n if ('iosched' in self._updatedattr or _load) and self.iosched<>IoSchedType.default:\\n params['iosched']=str(self.iosched)\\n if ('readahead' in self._updatedattr or _load) and self.readahead :\\n params['readahead']=self.readahead\\n if params:\\n for pt in self.paths():\\n pt.provider.set_dev_params(pt,params)\",\n \"def onUpdate(self):\\n\\t\\t#fill all the order that satisfied\\n\\t\\tfor x in filter(self.isFilled,self().keys()):\\n\\t\\t\\tself[x].fill()\",\n \"def filled(self, *args, **kwargs):\\n out = getcopy(self)\\n out.fill(*args, **kwargs)\\n return out\",\n \"def fit_params(self, rfl_meas, geom, *args):\\n\\n return np.array([])\",\n \"def set_params(self, params: Dict) -> None:\\n self.leak.set_g(params['g_leak'])\\n self.nav.set_g(params['g_nav'])\\n self.kvhh.set_g(params['g_kvhh'])\\n self.kva.set_g(params['g_kva'])\\n self.kvsi.set_g(params['g_kvsi'])\\n self.cav.set_g(params['g_cav'])\\n self.kca.set_g(params['g_kca'])\\n self.nap.set_g(params['g_nap'])\\n self.kir.set_g(params['g_kir'])\\n self.ampar.set_g(params['g_ampar'])\\n self.nmdar.set_g(params['g_nmdar'])\\n self.gabar.set_g(params['g_gabar'])\\n self.tau_ca = params['t_ca']\",\n \"def expand_params(self):\\n \\n no_datasets = len(self.traces)\\n no_species = self.reaction_matrix.shape[0]\\n \\n t0_keys = [key for key in self.input_params.keys() if 't0' in key]\\n od_keys = [key for key in self.input_params.keys() if 'OD' in key]\\n k_keys = [key for key in self.input_params.keys() if 'k' in key]\\n c0_keys = [key for key in self.input_params.keys() if 'c0' in key]\\n \\n enum_keys = list(enumerate(self.input_params.keys()))\\n first_t0 = next(i for i,key in enum_keys if 't0' in key)\\n first_od = next(i for i,key in enum_keys if 'OD' in key)\\n first_k = next(i for i,key in enum_keys if 'k' in key)\\n first_c0 = next(i for i,key in enum_keys if 'c0' in key)\\n \\n t0_params = [self.input_params.pop(k) for k in t0_keys]\\n od_params = [self.input_params.pop(k) for k in od_keys]\\n k_params = [self.input_params.pop(k) for k in k_keys]\\n c0_params = [self.input_params.pop(k) for k in c0_keys]\\n \\n if len(t0_keys) == 1 and t0_keys[0] == 't0': \\n p = t0_params[0]\\n new_t0_params = [] \\n for d in range(1,no_datasets+1):\\n new_p = copy.deepcopy(p)\\n new_p.name += str(d)\\n new_t0_params.append(new_p)\\n t0_params = new_t0_params\\n \\n if len(od_keys) == 1 and od_keys[0] == 'OD_offset': \\n p = od_params[0]\\n new_od_params = []\\n for d in range(1,no_datasets+1):\\n new_p = copy.deepcopy(p)\\n new_p.name += str(d)\\n new_od_params.append(new_p)\\n od_params = new_od_params\\n \\n # TODO - this is not adequate - what if the first rate parameter \\n # isn't k1?\\n if len(k_keys) == self.reaction_matrix.sum() and k_keys[0] == 'k1':\\n new_k_params = []\\n for p in k_params:\\n for d in range(1,no_datasets+1):\\n new_p = copy.deepcopy(p) \\n new_p.name += str(d)\\n new_k_params.append(new_p)\\n k_params = new_k_params\\n \\n if len(c0_keys) == no_species and c0_keys[0] == 'c01':\\n new_c0_params = []\\n for p in c0_params:\\n for d in range(1,no_datasets+1):\\n new_p = copy.deepcopy(p)\\n new_p.name += str(d)\\n new_c0_params.append(new_p)\\n c0_params = new_c0_params\\n \\n # as lmfit parameters objects are ordered dictionaries the order\\n # that we do this actually matters and will influence the fitting\\n # we would like to allow the used to specify the order and respect the \\n # order they choose.\\n \\n # NB The ideal order is to have the parameters whos initial values are \\n # better optimised after the parameters whos initial values are worse \\n \\n expanded_params = sorted([(t0_params,first_t0),\\n (od_params,first_od),\\n (k_params,first_k),\\n (c0_params,first_c0)], key=lambda e:e[1])\\n expanded_params, loc = zip(*expanded_params)\\n \\n for ep in expanded_params:\\n self.input_params.add_many(*ep)\",\n \"def _reset_parameters(self) -> None:\\n self._setup_input = {\\n \\\"P\\\": csc_matrix(2.0 * self.opt.P(self.p).toarray()),\\n \\\"q\\\": self.opt.q(self.p).toarray().flatten(),\\n }\\n if self.opt_type in CONSTRAINED_OPT:\\n A = self.opt.A(self.p)\\n b = self.opt.b(self.p)\\n self._setup_input[\\\"A\\\"] = csc_matrix(\\n cs.vertcat(self.opt.M(self.p), A, -A).toarray()\\n )\\n self._setup_input[\\\"l\\\"] = (\\n cs.vertcat(-self.opt.c(self.p), -b, b).toarray().flatten()\\n )\",\n \"def set_params_BS(self):\\n params = self.ctx.input_params_KKR\\n\\n # maybe overwrite some inputs\\n if 'params_kkr_overwrite' in self.inputs:\\n self.report(f'found params_kkr_overwrite: {self.inputs.params_kkr_overwrite.get_dict()}')\\n updatenode = self.inputs.params_kkr_overwrite\\n updatenode.label = 'params overwrite'\\n params = update_params_wf(params, updatenode)\\n\\n input_dict = params.get_dict()\\n para_check = kkrparams()\\n try:\\n for key, val in input_dict.items():\\n para_check.set_value(key, val, silent=True)\\n except:\\n return self.exit_codes.ERROR_CALC_PARAMETERS_INVALID # pylint: disable=no-member\\n label = ''\\n descr = f'(pk - {self.inputs.remote_data.pk}, and uuid - {self.inputs.remote_data.uuid})'\\n\\n missing_list = para_check.get_missing_keys(use_aiida=True)\\n\\n if missing_list != []:\\n kkrdefaults = kkrparams.get_KKRcalc_parameter_defaults()[0]\\n kkrdefaults_updated = []\\n for key_default, val_default in list(kkrdefaults.items()):\\n if key_default in missing_list:\\n para_check.set_value(key_default, val_default)\\n kkrdefaults_updated.append(key_default)\\n missing_list.remove(key_default)\\n if len(missing_list) > 0:\\n self.report(f'ERROR: calc_parameters misses keys: {missing_list}')\\n return self.exit_codes.ERROR_CALC_PARAMETERS_INCOMPLETE # pylint: disable=no-member\\n else:\\n self.report(f'updated KKR parameter node with default values: {kkrdefaults_updated}')\\n label = 'add_defaults_'\\n descr = 'added missing default keys, '\\n ##+++ Starts to add the NTP2, EMAX and EMIN from the\\n econt_new = self.ctx.BS_params_dict\\n if self.ctx.struc_is_alloy:\\n if econt_new.get('kmesh', None) is None:\\n econt_new['kmesh'] = [1, 1, 1] # overwrite kmesh since the kpoints are used from the input\\n kkr_calc = self.inputs.remote_data.get_incoming(node_class=KkrCalculation).first().node\\n ef = kkr_calc.outputs.output_parameters.get_dict()['fermi_energy'] # unit in Ry\\n self.ctx.fermi_energy = ef ## in Ry unit\\n\\n # Set BS params\\n try:\\n para_check = set_energy_params(econt_new, ef, para_check)\\n except:\\n return self.exit_codes.ERROR_CALC_PARAMETERS_INVALID # pylint: disable=no-member\\n\\n para_check.set_multiple_values(\\n NPT1=0,\\n NPT3=0,\\n NPOL=0,\\n )\\n\\n updatenode = Dict(para_check.get_dict())\\n updatenode.label = label + 'KKRparam_BS'\\n updatenode.description = 'KKR parameter node extracted from remote_folder' + descr + ' as well as wf_parameter input node.'\\n\\n paranode_BS = update_params_wf(self.ctx.input_params_KKR, updatenode)\\n self.ctx.BS_kkrparams = paranode_BS\",\n \"def addParameters(self):\\n\\n self.pRefArray = self.addParam(\\\"ikrefarray\\\", \\\"string\\\", \\\"\\\")\\n self.pUseIndex = self.addParam(\\\"useIndex\\\", \\\"bool\\\", False)\\n\\n self.pParentJointIndex = self.addParam(\\n \\\"parentJointIndex\\\", \\\"long\\\", -1, None, None)\\n\\n self.pJoint = self.addParam(\\\"joint\\\", \\\"bool\\\", True)\",\n \"def set_params(self, params):\\n for step_id, step_params in _iteritems(params):\\n for name, value in _iteritems(step_params):\\n self.add_param(step_id, name, value)\",\n \"def _fillData(self, extras):\\n e = {k : (\\\" \\\".join(v[\\\"words\\\"])\\n if type(v) == dict and \\\"words\\\" in v else v) for k, v in extras.items()}\\n return self.data % e\",\n \"def fill_item(self, args, producing_job):\\n pass\",\n \"def set_params(self, params: Dict) -> None:\\n self.leak.set_g(params[\\\"g_leak\\\"])\\n self.kvhh.set_g(params[\\\"g_kvhh\\\"])\\n self.cav.set_g(params[\\\"g_cav\\\"])\\n self.kca.set_g(params[\\\"g_kca\\\"])\\n self.nap.set_g(params[\\\"g_nap\\\"])\\n self.tau_ca = params[\\\"t_ca\\\"]\",\n \"def set_params(self, dic):\\n if dic is not None:\\n for key, val in zip(dic.keys(), dic.values()):\\n if key in self.__dict__.keys():\\n self.__dict__[key] = val\\n\\n if 'scale_params' in self.__dict__.keys():\\n self.scale_params.set_params(dic)\\n if 'atmospheric_params' in self.__dict__.keys():\\n if self.atmospheric_params is not None:\\n self.atmospheric_params.set_params(dic)\\n\\n if 'atemperature_params' in self.__dict__.keys():\\n if self.atemperature_params is not None:\\n self.atemperature_params.set_params(dic)\\n\\n if 'oceanic_params' in self.__dict__.keys():\\n if self.oceanic_params is not None:\\n self.oceanic_params.set_params(dic)\\n\\n if 'ground_params' in self.__dict__.keys():\\n if self.ground_params is not None:\\n self.ground_params.set_params(dic)\\n\\n if 'otemperature_params' in self.__dict__.keys():\\n if self.gotemperature_params is not None:\\n self.gotemperature_params.set_params(dic)\\n\\n if 'gtemperature_params' in self.__dict__.keys():\\n if self.gotemperature_params is not None:\\n self.gotemperature_params.set_params(dic)\",\n \"def add_data(self,**kwargs):\\n self.given_data.update([x for x in kwargs.keys() if kwargs[x]!=None ])\\n for i in range(len(self.attr)):\\n param=self.attr[i]\\n if param in kwargs and kwargs[param]!=None:\\n if i==0 and not (0 <= kwargs['angle'] <= 90) :# atribute is angle\\n raise ValueError('Angle should be between 0 an 90 degrees')\\n elif i==7 and not (0 <= kwargs[param] <= 1):\\n raise ValueError('Coefficient (kf) should be between 0 and 1')\\n else:\\n self.data[param]=kwargs[param]\\n print('Added data to object. See current data by using print(object_name) or using check_data method')\",\n \"def set_parameters(self, full=None, r=None, l=None, d=None, z=None):\\n\\n original = _deepcopy(self.parameters) # save in case of error\\n\\n if type(full) is bool:\\n self.parameters[\\\"full\\\"] = full\\n if type(r) in [int, float]:\\n self.parameters[\\\"r\\\"] = float(r)\\n if self._type == 2: # observation well\\n if type(d) in [int, float]:\\n self.parameters[\\\"d\\\"] = float(d)\\n if type(l) in [int, float]:\\n self.parameters[\\\"l\\\"] = float(l)\\n else: # piezometer\\n if type(z) in [int, float]:\\n self.parameters[\\\"z\\\"] = float(z)\\n\\n flag, message = self.validate_parameters()\\n if not flag:\\n print(message)\\n self.parameters.update(original)\\n # End Function\",\n \"def _populate_default_values(self):\\n\\n if 'input_data' not in self._definition:\\n self._definition['input_data'] = []\\n for input_dict in self._definition['input_data']:\\n if 'required' not in input_dict:\\n input_dict['required'] = True\\n\\n if 'jobs' not in self._definition:\\n self._definition['jobs'] = []\\n for job_dict in self._definition['jobs']:\\n if 'recipe_inputs' not in job_dict:\\n job_dict['recipe_inputs'] = []\\n if 'dependencies' not in job_dict:\\n job_dict['dependencies'] = []\\n for dependency_dict in job_dict['dependencies']:\\n if 'connections' not in dependency_dict:\\n dependency_dict['connections'] = []\",\n \"def __prepare_dh_params(self):\\n self.alpha = symbols('alpha0:' + str(self.joint_count))\\n self.a = symbols('a0:' + str(self.joint_count))\\n self.q = symbols('q1:' + str(self.joint_count + 1))\\n self.d = symbols('d1:' + str(self.joint_count + 1))\",\n \"def set_params(self, *, params: Params) -> None: # pragma: no cover\\n\\t\\tsuper().set_params(params=params)\",\n \"def monkey_set_f_params(self):\\n self._monkey_set_f_params_counter += 1\",\n \"def monkey_set_f_params(self):\\n self._monkey_set_f_params_counter += 1\",\n \"def get_complete_parameters(self, auth_request_params):\\n params = super().get_complete_parameters(auth_request_params)\\n params.update(\\n {\\n \\\"id_token\\\": sign_id_token(self.get_apple_id_token_payload()),\\n \\\"user\\\": json.dumps(\\n {\\n \\\"email\\\": \\\"private@appleid.apple.com\\\",\\n \\\"name\\\": {\\n \\\"firstName\\\": \\\"A\\\",\\n \\\"lastName\\\": \\\"B\\\",\\n },\\n }\\n ),\\n }\\n )\\n return params\",\n \"def _autoInitPars(self):\\n for p in self._pars:\\n setattr(self,p,self.defaultparval)\",\n \"def set_params(self, **params):\\n if('threshold' in params.keys()):\\n self.threshold = params['threshold']\\n if('subsample' in params.keys()):\\n self.subsample = params['subsample']\\n if('estimator' in params.keys()):\\n self.estimator = params['estimator']\\n if('n_folds' in params.keys()):\\n self.n_folds = params['n_folds']\\n if('stratify' in params.keys()):\\n self.stratify = params['stratify']\\n if('random_state' in params.keys()):\\n self.random_state = params['random_state']\\n if('n_jobs' in params.keys()):\\n self.n_jobs = params['n_jobs']\",\n \"def params(self,new):\\n self._params = new\\n self._config_set()\\n self._make_model()\",\n \"def add_params(self, params):\\n return self.set_param('params', params)\",\n \"def set_scan_params(self, session, params):\\n if params['reset']:\\n self._set_default_scan_params()\\n for k in ['az_speed', 'az_accel']:\\n if params[k] is not None:\\n self.scan_params[k] = params[k]\\n self.log.info('Updated default scan params to {sp}', sp=self.scan_params)\\n yield\\n return True, 'Done'\",\n \"def apply_filling(data, filling_list):\\n method_name = filling_list[0][MethodKeys.METHOD]\\n method_params = filling_list[0][MethodKeys.PARAMETERS]\\n return NonSeqFillingMethods.get_method(method_name)(**method_params)(\\n data)\",\n \"def _register_global_params(self, params):\\n\\n for name,obj in self.params().items():\\n global_params.add(**{name:obj})\\n\\n for name,val in params.items():\\n global_params.params(name).default=val\\n\\n params.update(global_params.get_param_values())\\n params[\\\"name\\\"]=self.name\",\n \"def set_params(self, **kargs):\\n\\n # may further modify parameters manually\\n if len(kargs) > 0:\\n for key in kargs:\\n if key in self.params[self.profile].keys():\\n self.params[self.profile][key] = kargs[key]\\n else:\\n print '%s not a standard key. Will not be used.' % (key)\\n \\n self.pathout = self.params[self.profile]['pathout']\\n self.chans = self.params[self.profile]['chans']\\n self.dmarr = self.params[self.profile]['dmarr']\\n self.pulsewidth = self.params[self.profile]['pulsewidth'] * n.ones(len(self.chans))\\n self.approxuvw = self.params[self.profile]['approxuvw']\\n self.beam_params = self.params[self.profile]['beam_params']\\n self.long = self.params[self.profile]['long']\\n self.lat = self.params[self.profile]['lat']\",\n \"def _fill_experiment_parameters(self, prediction_type: str, prediction_column: str, holdout_size: float,\\n csv_separator: str = ',', excel_sheet: Union[str, int] = 0,\\n encoding: str = 'utf-8') -> None:\\n self.auto_pipeline_params = {\\n 'prediction_type': prediction_type,\\n 'prediction_column': prediction_column,\\n 'holdout_size': holdout_size,\\n 'csv_separator': csv_separator,\\n 'excel_sheet': excel_sheet,\\n 'encoding': encoding\\n }\",\n \"def update_parameters(self,like_params):\\n\\n # get current dictionary with parameters, update and setup again\\n params=self.get_params()\\n\\n for par in like_params:\\n if par.name in params:\\n params[par.name]=par.value\\n\\n self._setup_from_parameters(params)\\n return\",\n \"def fill_args(cls, toolchain, parser):\\n pass # pass must be overloaded (if required)\",\n \"def _populate_params(self):\\n self.params = []\\n for root, dirs, files in os.walk(os.curdir):\\n for file in files:\\n fullfile = str(os.path.join(root, file))\\n if self.config.regex_find_params.match(fullfile):\\n self.params.append(fullfile)\",\n \"def check_data(self):\\n\\n missing_params = {}\\n flag = False\\n\\n missing_params['general'] = {}\\n for name, param in self.params.items():\\n if not param.check():\\n missing_params['general'][name] = param.get_description()\\n flag = True\\n\\n for component, comp_obj in self.components.items():\\n missing_params[component], flag_comp = comp_obj.check_data()\\n\\n # Assign empty component parameters that have a general version:\\n empty_general_params = set(missing_params[component]).intersection(\\n set(self.params))\\n for param in empty_general_params:\\n comp_obj.change_param_object(param, self.params[param])\\n del missing_params[component][param]\\n\\n if missing_params[component]:\\n flag = True\\n\\n if flag:\\n raise Exception('Following parameters are missing:\\\\n{}'\\n .format(\\n self._print_params(missing_params, disp=False)))\\n\\n return True\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6528969","0.63597214","0.6197034","0.61547756","0.6130784","0.61055094","0.6097497","0.5999343","0.59145826","0.5904964","0.5889323","0.5852561","0.58364487","0.58171743","0.57736933","0.5735036","0.5718243","0.56878495","0.56824","0.56730765","0.56705946","0.5666754","0.56557995","0.5630812","0.5600198","0.55701536","0.55692935","0.5566039","0.55612606","0.55549914","0.55539346","0.55402684","0.55402684","0.55314225","0.5520128","0.5503423","0.5491206","0.5484494","0.54824036","0.5474092","0.5467326","0.54655474","0.54552996","0.54454863","0.54445505","0.5441708","0.54079026","0.53969944","0.5392164","0.5385328","0.53826964","0.5381703","0.53653896","0.53630054","0.53583497","0.53489745","0.5345118","0.53385276","0.533304","0.53321123","0.5319022","0.53184557","0.53160113","0.5313904","0.53073585","0.53061","0.5299041","0.52815014","0.5276989","0.52741474","0.5274118","0.5262896","0.5262737","0.5255421","0.52524006","0.5248638","0.5248368","0.52456975","0.52291155","0.52116215","0.52038515","0.52008295","0.5200123","0.5197647","0.5197583","0.5197531","0.5197531","0.5196881","0.5194164","0.5191046","0.5190512","0.51878476","0.5184799","0.5183422","0.5182903","0.51812977","0.51747966","0.51725084","0.5171105","0.5165115","0.5163137"],"string":"[\n \"0.6528969\",\n \"0.63597214\",\n \"0.6197034\",\n \"0.61547756\",\n \"0.6130784\",\n \"0.61055094\",\n \"0.6097497\",\n \"0.5999343\",\n \"0.59145826\",\n \"0.5904964\",\n \"0.5889323\",\n \"0.5852561\",\n \"0.58364487\",\n \"0.58171743\",\n \"0.57736933\",\n \"0.5735036\",\n \"0.5718243\",\n \"0.56878495\",\n \"0.56824\",\n \"0.56730765\",\n \"0.56705946\",\n \"0.5666754\",\n \"0.56557995\",\n \"0.5630812\",\n \"0.5600198\",\n \"0.55701536\",\n \"0.55692935\",\n \"0.5566039\",\n \"0.55612606\",\n \"0.55549914\",\n \"0.55539346\",\n \"0.55402684\",\n \"0.55402684\",\n \"0.55314225\",\n \"0.5520128\",\n \"0.5503423\",\n \"0.5491206\",\n \"0.5484494\",\n \"0.54824036\",\n \"0.5474092\",\n \"0.5467326\",\n \"0.54655474\",\n \"0.54552996\",\n \"0.54454863\",\n \"0.54445505\",\n \"0.5441708\",\n \"0.54079026\",\n \"0.53969944\",\n \"0.5392164\",\n \"0.5385328\",\n \"0.53826964\",\n \"0.5381703\",\n \"0.53653896\",\n \"0.53630054\",\n \"0.53583497\",\n \"0.53489745\",\n \"0.5345118\",\n \"0.53385276\",\n \"0.533304\",\n \"0.53321123\",\n \"0.5319022\",\n \"0.53184557\",\n \"0.53160113\",\n \"0.5313904\",\n \"0.53073585\",\n \"0.53061\",\n \"0.5299041\",\n \"0.52815014\",\n \"0.5276989\",\n \"0.52741474\",\n \"0.5274118\",\n \"0.5262896\",\n \"0.5262737\",\n \"0.5255421\",\n \"0.52524006\",\n \"0.5248638\",\n \"0.5248368\",\n \"0.52456975\",\n \"0.52291155\",\n \"0.52116215\",\n \"0.52038515\",\n \"0.52008295\",\n \"0.5200123\",\n \"0.5197647\",\n \"0.5197583\",\n \"0.5197531\",\n \"0.5197531\",\n \"0.5196881\",\n \"0.5194164\",\n \"0.5191046\",\n \"0.5190512\",\n \"0.51878476\",\n \"0.5184799\",\n \"0.5183422\",\n \"0.5182903\",\n \"0.51812977\",\n \"0.51747966\",\n \"0.51725084\",\n \"0.5171105\",\n \"0.5165115\",\n \"0.5163137\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":9199,"cells":{"query":{"kind":"string","value":"Filled name (if applicable)."},"document":{"kind":"string","value":"def filled(self):\n if self.parent in filled_variables:\n return f\"{self._fill_root} {self.shift}M\"\n return self._fill_root"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def name(self, name):\n pass","def name():\n pass","def name():\n pass","def getName(self):\n return \"\"","def name_field(self):\r\n return 'name'","def test_name_empty_string(self):\r\n self.name = \"\"","def name(self) -> str: # pragma: no cover","def name(self) -> Optional[str]:\n ...","def start_name(self, attributes):\n self.name = True","def name(self):\r\n pass","def name(self) -> str:","def name(self) -> str:","def name(self) -> str:","def name(self) -> str:","def name(self) -> str:","def Name(self) -> str:","def Name(self) -> str:","def Name(self) -> str:","def Name(self) -> str:","def name():\n\n pass","def name(self) -> str | None:\n pass","def name(self) -> str:\n ...","def name(self) -> str:\n ...","def name(self):\r\n return None","def name(self):\n ...","def name(self):\n pass","def set_name(self, name=\"\"):\n if isinstance(name, str):\n self.__name = name\n return 0\n print(\"type of nom is not STR\")\n return 1","def __init__(__self__, *,\n name: pulumi.Input[str]):\n pulumi.set(__self__, \"name\", name)","def name(self, name):\n self.__name = name","def name(self, value):\n self._name = c(value)","def name(self, name: str):\r\n self._name = name","def name(self, name: str):\r\n self._name = name","def name(self, name: str):\r\n self._name = name","def name(self, name: str):\r\n self._name = name","def set_name(self, name):\n\t\tself.name_ = name","def __init__(self, name):\r\n self.name = name # type is str\r","def enter_name(self, name):\n self.name = name","def name(self):","def name(self):","def name(self):","def name(self):","def name() -> str:\n pass","def name(self) -> str:\n pass","def name(self) -> str:\n pass","def name(self) -> str:\n pass","def name(self) -> str:\n pass","def __init__(self, name):\n self.name = name.replace(\" \", \"-\").lower()","def name(self, name):\n \n if name is not None and len(name) > 32: \n raise ValueError(\"Invalid value for `name`, length must be less than `32`\")\n\n self._name = name","def __init__(self, name: Optional[str] = None):\n self.name = name","def test_name_mandatory(self):\n field = self.base_field\n del field['name']\n with self.assertRaises(FieldSchemaError):\n SchemaField(field)\n # no blank\n field = self.base_field\n field['name'] = ''\n with self.assertRaises(FieldSchemaError):\n SchemaField(field)","def name(self, name: str) -> None:\n self._name = name","def name(self, value):\n\n if value is not None:\n assert is_string(value), (\n ('\"{0}\" attribute: \"{1}\" is not a \"string\" like object!'\n ).format('name', value))\n self._name = value","def set_name(self, newname=\"\"):\n self.name = newname","def Name(self, name):\r\n\r\n self.name = name\r\n return self","def __init__(self, name: str) -> None:\n self._name = name","def name(self, value: str) -> None:\n self._name = value","def name(self, name) :\n\t\ttry :\n\t\t\tself._name = name\n\t\texcept Exception as e:\n\t\t\traise e","def __init__(self, name: str):\n self.name = name","def name_value(self) -> global___Expression.NameValue:","def fix_name(self):\n self._name_fixed = True","def name(self):\n return None","def __init__(self, name):\n self._name = name\n pass","def test_name_set(self):\n name = \"Field Name\"\n field = basic.flag(name=name)\n\n self.assertEqual(name, field.name)\n\n self.assertEqual(name, field.name)","def name(self):\n return 'Null'","def __init__(self, name = None):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def name(self, name):\n self._name = name","def generate(self, name):\n return ''","def get_name(self):\n name = input(\"What is your name? \")\n if len(name) > 0:\n self.name = name","def __init__(self, name, default=None, help=None):\n self._name = name.replace('-', '_')\n self._value = default\n self._default = default\n self._help = help","def name(self, value):\n self._name = value","def name(self, value):\n self._name = value","def __init__(self, name):\n self._name = name","def __init__(self, name):\n self._name = name","def set_name(self,name):\r\n self._name = __name","def __init__(self,name=\"\"):\n self.name = name\n self.dirty = False\n self.reset()","def __init__(self, name):\r\n self.name = name","def __init__(self):\n self.__name = 'name'","def name(self) -> unicode:\n ...","def __init__(self, name= None):\n self.name = name","def __init__(__self__, *,\n name: Optional[pulumi.Input[str]] = None):\n if name is not None:\n pulumi.set(__self__, \"name\", name)","def __init__(__self__, *,\n name: Optional[pulumi.Input[str]] = None):\n if name is not None:\n pulumi.set(__self__, \"name\", name)","def __init__(__self__, *,\n name: Optional[pulumi.Input[str]] = None):\n if name is not None:\n pulumi.set(__self__, \"name\", name)","def __init__(__self__, *,\n name: Optional[pulumi.Input[str]] = None):\n if name is not None:\n pulumi.set(__self__, \"name\", name)","def __init__(__self__, *,\n name: Optional[pulumi.Input[str]] = None):\n if name is not None:\n pulumi.set(__self__, \"name\", name)","def __init__(__self__, *,\n name: Optional[pulumi.Input[str]] = None):\n if name is not None:\n pulumi.set(__self__, \"name\", name)","def name(self): # -> Any | str:\n ...","def name(self):\n return NotImplemented","def name(self, name):\n if name is not None and len(name) > 255:\n raise ValueError(\"Invalid value for `name`, length must be less than or equal to `255`\")\n if name is not None and len(name) < 3:\n raise ValueError(\"Invalid value for `name`, length must be greater than or equal to `3`\")\n\n self._name = name","def __init__(self, name: str = 'ret_val') -> None:\n self.name = name\n self.class_name = \"\"","def _check_name(self):\n\t\tpass"],"string":"[\n \"def name(self, name):\\n pass\",\n \"def name():\\n pass\",\n \"def name():\\n pass\",\n \"def getName(self):\\n return \\\"\\\"\",\n \"def name_field(self):\\r\\n return 'name'\",\n \"def test_name_empty_string(self):\\r\\n self.name = \\\"\\\"\",\n \"def name(self) -> str: # pragma: no cover\",\n \"def name(self) -> Optional[str]:\\n ...\",\n \"def start_name(self, attributes):\\n self.name = True\",\n \"def name(self):\\r\\n pass\",\n \"def name(self) -> str:\",\n \"def name(self) -> str:\",\n \"def name(self) -> str:\",\n \"def name(self) -> str:\",\n \"def name(self) -> str:\",\n \"def Name(self) -> str:\",\n \"def Name(self) -> str:\",\n \"def Name(self) -> str:\",\n \"def Name(self) -> str:\",\n \"def name():\\n\\n pass\",\n \"def name(self) -> str | None:\\n pass\",\n \"def name(self) -> str:\\n ...\",\n \"def name(self) -> str:\\n ...\",\n \"def name(self):\\r\\n return None\",\n \"def name(self):\\n ...\",\n \"def name(self):\\n pass\",\n \"def set_name(self, name=\\\"\\\"):\\n if isinstance(name, str):\\n self.__name = name\\n return 0\\n print(\\\"type of nom is not STR\\\")\\n return 1\",\n \"def __init__(__self__, *,\\n name: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def name(self, name):\\n self.__name = name\",\n \"def name(self, value):\\n self._name = c(value)\",\n \"def name(self, name: str):\\r\\n self._name = name\",\n \"def name(self, name: str):\\r\\n self._name = name\",\n \"def name(self, name: str):\\r\\n self._name = name\",\n \"def name(self, name: str):\\r\\n self._name = name\",\n \"def set_name(self, name):\\n\\t\\tself.name_ = name\",\n \"def __init__(self, name):\\r\\n self.name = name # type is str\\r\",\n \"def enter_name(self, name):\\n self.name = name\",\n \"def name(self):\",\n \"def name(self):\",\n \"def name(self):\",\n \"def name(self):\",\n \"def name() -> str:\\n pass\",\n \"def name(self) -> str:\\n pass\",\n \"def name(self) -> str:\\n pass\",\n \"def name(self) -> str:\\n pass\",\n \"def name(self) -> str:\\n pass\",\n \"def __init__(self, name):\\n self.name = name.replace(\\\" \\\", \\\"-\\\").lower()\",\n \"def name(self, name):\\n \\n if name is not None and len(name) > 32: \\n raise ValueError(\\\"Invalid value for `name`, length must be less than `32`\\\")\\n\\n self._name = name\",\n \"def __init__(self, name: Optional[str] = None):\\n self.name = name\",\n \"def test_name_mandatory(self):\\n field = self.base_field\\n del field['name']\\n with self.assertRaises(FieldSchemaError):\\n SchemaField(field)\\n # no blank\\n field = self.base_field\\n field['name'] = ''\\n with self.assertRaises(FieldSchemaError):\\n SchemaField(field)\",\n \"def name(self, name: str) -> None:\\n self._name = name\",\n \"def name(self, value):\\n\\n if value is not None:\\n assert is_string(value), (\\n ('\\\"{0}\\\" attribute: \\\"{1}\\\" is not a \\\"string\\\" like object!'\\n ).format('name', value))\\n self._name = value\",\n \"def set_name(self, newname=\\\"\\\"):\\n self.name = newname\",\n \"def Name(self, name):\\r\\n\\r\\n self.name = name\\r\\n return self\",\n \"def __init__(self, name: str) -> None:\\n self._name = name\",\n \"def name(self, value: str) -> None:\\n self._name = value\",\n \"def name(self, name) :\\n\\t\\ttry :\\n\\t\\t\\tself._name = name\\n\\t\\texcept Exception as e:\\n\\t\\t\\traise e\",\n \"def __init__(self, name: str):\\n self.name = name\",\n \"def name_value(self) -> global___Expression.NameValue:\",\n \"def fix_name(self):\\n self._name_fixed = True\",\n \"def name(self):\\n return None\",\n \"def __init__(self, name):\\n self._name = name\\n pass\",\n \"def test_name_set(self):\\n name = \\\"Field Name\\\"\\n field = basic.flag(name=name)\\n\\n self.assertEqual(name, field.name)\\n\\n self.assertEqual(name, field.name)\",\n \"def name(self):\\n return 'Null'\",\n \"def __init__(self, name = None):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def name(self, name):\\n self._name = name\",\n \"def generate(self, name):\\n return ''\",\n \"def get_name(self):\\n name = input(\\\"What is your name? \\\")\\n if len(name) > 0:\\n self.name = name\",\n \"def __init__(self, name, default=None, help=None):\\n self._name = name.replace('-', '_')\\n self._value = default\\n self._default = default\\n self._help = help\",\n \"def name(self, value):\\n self._name = value\",\n \"def name(self, value):\\n self._name = value\",\n \"def __init__(self, name):\\n self._name = name\",\n \"def __init__(self, name):\\n self._name = name\",\n \"def set_name(self,name):\\r\\n self._name = __name\",\n \"def __init__(self,name=\\\"\\\"):\\n self.name = name\\n self.dirty = False\\n self.reset()\",\n \"def __init__(self, name):\\r\\n self.name = name\",\n \"def __init__(self):\\n self.__name = 'name'\",\n \"def name(self) -> unicode:\\n ...\",\n \"def __init__(self, name= None):\\n self.name = name\",\n \"def __init__(__self__, *,\\n name: Optional[pulumi.Input[str]] = None):\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def __init__(__self__, *,\\n name: Optional[pulumi.Input[str]] = None):\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def __init__(__self__, *,\\n name: Optional[pulumi.Input[str]] = None):\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def __init__(__self__, *,\\n name: Optional[pulumi.Input[str]] = None):\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def __init__(__self__, *,\\n name: Optional[pulumi.Input[str]] = None):\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def __init__(__self__, *,\\n name: Optional[pulumi.Input[str]] = None):\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def name(self): # -> Any | str:\\n ...\",\n \"def name(self):\\n return NotImplemented\",\n \"def name(self, name):\\n if name is not None and len(name) > 255:\\n raise ValueError(\\\"Invalid value for `name`, length must be less than or equal to `255`\\\")\\n if name is not None and len(name) < 3:\\n raise ValueError(\\\"Invalid value for `name`, length must be greater than or equal to `3`\\\")\\n\\n self._name = name\",\n \"def __init__(self, name: str = 'ret_val') -> None:\\n self.name = name\\n self.class_name = \\\"\\\"\",\n \"def _check_name(self):\\n\\t\\tpass\"\n]","isConversational":false},"negative_scores":{"kind":"list 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\"0.69951504\",\n \"0.6751056\",\n \"0.6751056\",\n \"0.67024434\",\n \"0.6659543\",\n \"0.6640836\",\n \"0.65940964\",\n \"0.65553534\",\n \"0.65237314\",\n \"0.6510735\",\n \"0.64991957\",\n \"0.64991957\",\n \"0.64991957\",\n \"0.64991957\",\n \"0.64991957\",\n \"0.647957\",\n \"0.647957\",\n \"0.647957\",\n \"0.647957\",\n \"0.6468007\",\n \"0.6453826\",\n \"0.64439255\",\n \"0.64439255\",\n \"0.6427313\",\n \"0.6424\",\n \"0.64173114\",\n \"0.6413034\",\n \"0.6399842\",\n \"0.6389371\",\n \"0.63791126\",\n \"0.63751024\",\n \"0.63751024\",\n \"0.63751024\",\n \"0.63751024\",\n \"0.636025\",\n \"0.63469875\",\n \"0.633714\",\n \"0.6334183\",\n \"0.6334183\",\n \"0.6334183\",\n \"0.6334183\",\n \"0.6324776\",\n \"0.6324255\",\n \"0.6324255\",\n \"0.6324255\",\n \"0.6324255\",\n \"0.6312909\",\n \"0.6311944\",\n \"0.62996954\",\n \"0.62826216\",\n \"0.6279673\",\n \"0.627692\",\n \"0.627579\",\n \"0.62725896\",\n \"0.62709206\",\n \"0.6269881\",\n \"0.6268454\",\n \"0.626399\",\n 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\"0.6140577\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":91,"numItemsPerPage":100,"numTotalItems":95772,"offset":9100,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6Im1sR1pFYktIVHRVSGRhX1RRdEczQ0N1S3k5ME9Qd25DNHY5elRjM3FVYzgifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4Mjc3NDc2OCwianRpIjoiZmIxMDA5NjktNWQxNi00NmRhLWI3YTItMDkyYjU2ZDAwMTZjIiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODI3NzgzNjgsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.GtL5m5V6wPIjQKoQ4QyYMUWc0jHZK3lYIiF_SmS6kAfUpz9Hp0hhBlEgpmo1dSDVaxmDUEUPJxz1J3-Az8x6Dw","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Copied and modified from the official icetop_Level3_scripts | def rerun_reconstructions_snow_lambda(tray, snow_lambda):
SnowFactor = snow_lambda
name = 'processing'
# Remove the L2 reconstructions
tray.Add(level2_IceTop.RemoveOldLevel2, 'RemoveOldLevel2')
extra_keys = ['LaputopSnowDiagnostics',
'IceTopHLCSeedRTPulses_SnowCorrected',
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exo2():",
"def substantiate():",
"def falcon():",
"def CL(self):",
"def script(self):",
"def exercise_b2_106():\r\n pass",
"def exercise_b2_113():\r\n pass",
"def test_fobj():\n Level3File(get_test_data('nids/Level3_FFC_N0Q_20140407_1805.nids'))",
"def mezclar_bolsa(self):",
"def exe... | [
"0.60673505",
"0.57316786",
"0.57143044",
"0.56544286",
"0.55507493",
"0.5425385",
"0.53751373",
"0.53641415",
"0.5281127",
"0.52700067",
"0.5243484",
"0.5227051",
"0.5217968",
"0.5208976",
"0.51897764",
"0.517396",
"0.5118316",
"0.5114902",
"0.5114671",
"0.51113915",
"0.5110... | 0.0 | -1 |
Load the data which has been generated by the simulator from historic files | def get_candles_data(self):
df = pd.read_csv(f'realtime_data/data.csv', names=['date', 'open', 'high', 'low', 'close', 'volume', 'barCount', 'average'])
df = self.data_util_ref.pre_data_process(df)
output = self.visual_ref.get_candles_visual_data(df)
return json.dumps([output['data'][-4... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _load_state(self):\n \n if os.path.isfile(self.histFile):\n with open(self.histFile,'rb') as hf:\n oldFile = hf.read()\n \n if os.path.isfile(oldFile):\n self.dbFile.Value = oldFile",
"def load_(self):\n path = os.path.jo... | [
"0.70352036",
"0.70295185",
"0.69942",
"0.6906483",
"0.63878626",
"0.6382765",
"0.6270393",
"0.62033886",
"0.62032616",
"0.6193245",
"0.6143477",
"0.612875",
"0.6127106",
"0.6097942",
"0.60866916",
"0.6064095",
"0.6058584",
"0.60450536",
"0.6044156",
"0.60385203",
"0.6036894"... | 0.0 | -1 |
Load the data which has been generated by the simulator from historic files | def get_prediction_data(self):
df = pd.read_csv(f'realtime_data/data.csv', names=['date', 'open', 'high', 'low', 'close', 'volume', 'barCount', 'average'])
df = self.data_util_ref.pre_data_process(df)
output = self.visual_ref.get_prediction_visual_data(df)
# return json.dumps([output['d... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _load_state(self):\n \n if os.path.isfile(self.histFile):\n with open(self.histFile,'rb') as hf:\n oldFile = hf.read()\n \n if os.path.isfile(oldFile):\n self.dbFile.Value = oldFile",
"def load_(self):\n path = os.path.jo... | [
"0.70349073",
"0.7028908",
"0.69926465",
"0.69052213",
"0.6388666",
"0.6382003",
"0.6272473",
"0.6202085",
"0.6201776",
"0.6192213",
"0.61428773",
"0.61299187",
"0.6126348",
"0.6097556",
"0.6085418",
"0.60641634",
"0.60568464",
"0.60444623",
"0.6042505",
"0.6037602",
"0.60348... | 0.0 | -1 |
Checks the date and time, and then decides if a shift from master to slave (or vice versa) is needed. If necessary, makes the shift. | def main():
date = time.gmtime().tm_mday
if date == 1 or date == 2: # in case it missed once
# shift from slave to master, checking to ensure it hasn't already happened
status = check_status()
if status == 'slave':
slave_to_master()
elif status == 'master':
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __is_valid_move(self, scheduling_unit, turnus, date, person, overtime, depth=0, check_turnuses=[]):\n \n \n if not schedule_utils.is_valid_move (scheduling_unit, turnus, date, person, overtime):\n return False\n \n # if the workplace has the special rule: work in the afternoon, if the n... | [
"0.5707775",
"0.56430596",
"0.5583629",
"0.5324878",
"0.5245917",
"0.5093938",
"0.50450516",
"0.49869803",
"0.4892492",
"0.488806",
"0.4854944",
"0.485275",
"0.48295307",
"0.48010412",
"0.47898087",
"0.4774762",
"0.47731286",
"0.4770391",
"0.47576922",
"0.47565082",
"0.471500... | 0.74977547 | 0 |
Check the status of the application, i.e., whether it is running on the master or slave. Also check to see if there are any issues, like the web dyno on the slave running, or both workers running etc. | def check_status():
# assume no web dynos on master - there should never be a web dyno on master
r = req.get(f"{MASTER_API_URL}/formation/worker", headers=MASTER_API_HEADERS)
if r.status_code != req.codes.ok:
print("Couldn't get master worker formation")
print(r.status_code, ":", r.text)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_configuration_server(self) -> bool:\n return (\n self.container is not None\n and self.container.exec_run(\n \"bash -c 'curl -s --head http://localhost:19071/ApplicationStatus'\"\n )\n .output.decode(\"utf-8\")\n .split(\"\\r\\n... | [
"0.6630676",
"0.6584592",
"0.64988655",
"0.6488543",
"0.6485963",
"0.6476117",
"0.6447399",
"0.63786393",
"0.62928927",
"0.6289477",
"0.6250488",
"0.62484485",
"0.6197466",
"0.6183795",
"0.6161205",
"0.61303514",
"0.61219287",
"0.61159056",
"0.6114376",
"0.609758",
"0.6067191... | 0.6729618 | 0 |
Shift the process from master to slave, shifting data as needed. | def master_to_slave():
print("Shifting from master to slave")
stop_master_worker()
setup_slave_web()
prepare_push()
push_to_slave()
stop_slave_web()
start_slave_worker()
print("DONE!") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def slave_to_master():\n print(\"Shifting from slave to master\")\n stop_slave_worker()\n setup_slave_web()\n pull_from_slave()\n commit_pull_to_db()\n stop_slave_web()\n start_master_worker()\n print(\"DONE!\")",
"def runSlaveRun():\n\n np.set_printoptions(linewidth=1000)\n functio... | [
"0.72516125",
"0.5815426",
"0.567222",
"0.5663159",
"0.54625714",
"0.5429651",
"0.53810555",
"0.53091127",
"0.5294686",
"0.5285994",
"0.51691014",
"0.5157244",
"0.5134187",
"0.512011",
"0.50734735",
"0.50418085",
"0.5016566",
"0.5001079",
"0.4958527",
"0.49188",
"0.49104735",... | 0.7314937 | 0 |
Shift the process from slave to master, shifting data as needed. | def slave_to_master():
print("Shifting from slave to master")
stop_slave_worker()
setup_slave_web()
pull_from_slave()
commit_pull_to_db()
stop_slave_web()
start_master_worker()
print("DONE!") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def master_to_slave():\n print(\"Shifting from master to slave\")\n stop_master_worker()\n setup_slave_web()\n prepare_push()\n push_to_slave()\n stop_slave_web()\n start_slave_worker()\n print(\"DONE!\")",
"def write_master(self, data):\n self._write(self.master_fd, data)",
"def... | [
"0.72428024",
"0.5692221",
"0.56806463",
"0.55942285",
"0.5393446",
"0.5345593",
"0.53245896",
"0.53045934",
"0.5239213",
"0.5215958",
"0.5118116",
"0.5114614",
"0.50847006",
"0.5059445",
"0.5055491",
"0.5023818",
"0.5010442",
"0.5004643",
"0.49860305",
"0.49616227",
"0.49346... | 0.7228141 | 1 |
Sets up the web server on the slave, then checks it. | def setup_slave_web():
print("Starting slave web")
r = req.patch(f"{SLAVE_API_URL}/formation/web", json=API_PAYLOAD_1, headers=SLAVE_API_HEADERS)
if r.status_code != req.codes.ok:
print("Unable to start the web dyno on slave")
print(r.text)
return False
#wait a bit for the web pr... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup_server(manager):\n if not manager.is_daemon:\n return\n\n web_server_config = manager.config.get('web_server')\n\n if not web_server_config:\n return\n\n web_server = WebServer(\n bind=web_server_config['bind'],\n port=web_server_config['port'],\n )\n\n if we... | [
"0.6809068",
"0.67656696",
"0.6656338",
"0.6610853",
"0.65221626",
"0.6354455",
"0.62950474",
"0.6216161",
"0.62008417",
"0.62003654",
"0.6176954",
"0.601398",
"0.6004903",
"0.5986498",
"0.59861344",
"0.5985435",
"0.5959048",
"0.5956801",
"0.5941647",
"0.58429754",
"0.5814541... | 0.81821865 | 0 |
Stops the web process on the slave. | def stop_slave_web():
print("Stopping slave web")
r = req.patch(f"{SLAVE_API_URL}/formation/web", json=API_PAYLOAD_0, headers=SLAVE_API_HEADERS)
if r.status_code != req.codes.ok:
print("Unable to stop the web dyno on slave")
print(r.text)
return False
#wait a bit for the web proc... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def webserver_stop():\n run(\"kill $(cat %s)\" % GUNICORN_PIDFILE)\n run(\"rm %s\" % GUNICORN_PIDFILE)",
"def stop_slave_worker():\n print(\"Stopping slave worker\")\n r = req.patch(f\"{SLAVE_API_URL}/formation/worker\", json=API_PAYLOAD_0, headers=SLAVE_API_HEADERS)\n if r.status_code != req.code... | [
"0.7413745",
"0.7409462",
"0.70902383",
"0.7082552",
"0.68931115",
"0.68733066",
"0.68609893",
"0.6817112",
"0.67590433",
"0.67129856",
"0.6705761",
"0.6702287",
"0.66915804",
"0.6671726",
"0.6669743",
"0.6660702",
"0.66476685",
"0.66400963",
"0.6629474",
"0.6618239",
"0.6569... | 0.8396582 | 0 |
Starts the worker process on the master. | def start_master_worker():
print("Starting master worker")
r = req.patch(f"{MASTER_API_URL}/formation/worker", json=API_PAYLOAD_1, headers=MASTER_API_HEADERS)
if r.status_code != req.codes.ok:
print("Unable to start the worker dyno on master")
print(r.text)
return False
#wait a b... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def worker(ctx_obj):\n execute(start_worker_command(settings=ctx_obj['settings']))",
"def start(self):\n control_process = mp.Process(target = self._start, args = [])\n control_process.start()",
"def start_slave_worker():\n print(\"Starting slave worker\")\n r = req.patch(f\"{SLAVE_API_U... | [
"0.74038696",
"0.7210624",
"0.70151126",
"0.7001591",
"0.6949406",
"0.6915681",
"0.68317443",
"0.67932683",
"0.6752919",
"0.6713696",
"0.6707904",
"0.66620183",
"0.66078997",
"0.6578205",
"0.647364",
"0.6429986",
"0.63926333",
"0.6350077",
"0.6317507",
"0.6302991",
"0.6230232... | 0.7759477 | 0 |
Stops the worker process on the master. | def stop_master_worker():
print("Stopping master worker")
r = req.patch(f"{MASTER_API_URL}/formation/worker", json=API_PAYLOAD_0, headers=MASTER_API_HEADERS)
if r.status_code != req.codes.ok:
print("Unable to stop the worker dyno on master")
print(r.text)
return False
#wait a bit... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def stop(self):\n\n # immediate is necessary if it's in recovery (for now).\n # we don't care the result.\n master = gp.MasterStop(\"Stopping Master Standby\",\n self.datadir, mode='immediate')\n master.run()",
"def stop_slave_worker():\n print(\"Stopp... | [
"0.7388482",
"0.7279379",
"0.7237633",
"0.6967597",
"0.6921898",
"0.68627954",
"0.6821255",
"0.68206173",
"0.67904496",
"0.6728565",
"0.67254424",
"0.67202437",
"0.6709311",
"0.67050105",
"0.6670142",
"0.66601145",
"0.66253245",
"0.6620445",
"0.6605411",
"0.66041267",
"0.6577... | 0.76747125 | 0 |
Starts the worker process on the slave. | def start_slave_worker():
print("Starting slave worker")
r = req.patch(f"{SLAVE_API_URL}/formation/worker", json=API_PAYLOAD_1, headers=SLAVE_API_HEADERS)
if r.status_code != req.codes.ok:
print("Unable to start the worker dyno on slave")
print(r.text)
return False
#wait a bit fo... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def run_worker(self):\n # TODO(xiejw): To allow execution framework to add train hooks.\n return self._start_distributed_training()",
"def worker(ctx_obj):\n execute(start_worker_command(settings=ctx_obj['settings']))",
"def start_master_worker():\n print(\"Starting master worker\")\n r = req.pa... | [
"0.7050969",
"0.68271756",
"0.6755335",
"0.67251605",
"0.65629065",
"0.65401715",
"0.6436881",
"0.6374149",
"0.6337312",
"0.6323815",
"0.6307696",
"0.6272211",
"0.62686425",
"0.62494606",
"0.6231326",
"0.61917204",
"0.61633587",
"0.61614466",
"0.6132043",
"0.61305064",
"0.612... | 0.7931532 | 0 |
Stops the worker process on the slave. | def stop_slave_worker():
print("Stopping slave worker")
r = req.patch(f"{SLAVE_API_URL}/formation/worker", json=API_PAYLOAD_0, headers=SLAVE_API_HEADERS)
if r.status_code != req.codes.ok:
print("Unable to stop the worker dyno on slave")
print(r.text)
return False
#wait a bit for ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Stop(self):\n if self.child_pid:\n self.data = self.host.Communicate(self.child_pid, echo_error=True,\n kill=True,\n kill_string=IperfServer.KILL_STRING)\n self.child_pid = None",
"def stop(self):\n\n # immediat... | [
"0.7121769",
"0.7078228",
"0.70730764",
"0.703866",
"0.69969434",
"0.6940482",
"0.6888461",
"0.6873332",
"0.6864292",
"0.6846163",
"0.6844958",
"0.6808371",
"0.6796847",
"0.6751896",
"0.6735001",
"0.6733168",
"0.6719779",
"0.67189586",
"0.66959256",
"0.6666449",
"0.6627743",
... | 0.817291 | 0 |
Prepares to send data from master (this) to slave. | def prepare_push():
print("Preparing to push")
cur = conn.cursor()
try:
for tname in TABLES:
with open(f'{tname}.db', 'w') as f:
print(f"Copying {tname}")
cur.copy_to(f, f'"{tname}"')
return True
except IOError:
print("IO ERROR")
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def slave_to_master():\n print(\"Shifting from slave to master\")\n stop_slave_worker()\n setup_slave_web()\n pull_from_slave()\n commit_pull_to_db()\n stop_slave_web()\n start_master_worker()\n print(\"DONE!\")",
"def master_to_slave():\n print(\"Shifting from master to slave\")\n ... | [
"0.5962205",
"0.58612955",
"0.5847379",
"0.5833639",
"0.5828165",
"0.5792788",
"0.5755556",
"0.56804013",
"0.5674747",
"0.5459173",
"0.54531056",
"0.5439083",
"0.54315406",
"0.5406502",
"0.5381936",
"0.5331048",
"0.5322958",
"0.5303191",
"0.5276801",
"0.5276801",
"0.5276801",... | 0.0 | -1 |
Sends data from the master (this) to the slave. | def push_to_slave():
print("Pushing to slave")
try:
for tname in TABLES:
with open(f'{tname}.db', 'rb') as f:
print(f"Pushing {tname}")
r = req.post(f"{SLAVE_URL}/push_db/{tname}", files={'file': f}, data={'key': HMA_KEY})
if r.status_code != r... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def write_master(self, data):\n self._write(self.master_fd, data)",
"def send(self):\n if(self.target):\n try:\n self.message = self.message +\"\\r\\n\"\n self.target[0].send(self.message)\n except socket.error, err:\n print er... | [
"0.7521397",
"0.67997825",
"0.67381716",
"0.6720654",
"0.669663",
"0.6656692",
"0.6556619",
"0.65406233",
"0.6521673",
"0.6500805",
"0.6472015",
"0.6464885",
"0.6464885",
"0.6463158",
"0.6460335",
"0.6371669",
"0.6364468",
"0.6352487",
"0.63482475",
"0.633402",
"0.63125366",
... | 0.0 | -1 |
Pulls data from the slave. | def pull_from_slave():
print("Pulling from slave")
r = req.get(f"{SLAVE_URL}/prepare_pull")
if r.status_code != req.codes.ok:
print("Something wrong with slave on prepare pull")
print(r.text)
return False
print("Prepared")
try:
for tname in TABLES:
with op... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def _pull(self) -> None:\n raise NotImplementedError()",
"def pull(self):",
"def _pull(self) -> None:\n raise NotImplementedError() # pragma: no cover",
"def get_data(self):\n self._send_command(self._adapter.get_data())",
"def pull(self):\n raise NotImplementedError()",
... | [
"0.68342793",
"0.6720848",
"0.65273225",
"0.626639",
"0.61622834",
"0.61532104",
"0.6083716",
"0.601274",
"0.60006136",
"0.59574234",
"0.5846637",
"0.58430606",
"0.5761794",
"0.5746034",
"0.57344276",
"0.5729992",
"0.56974876",
"0.5640078",
"0.5632374",
"0.5596392",
"0.555516... | 0.67073804 | 2 |
Commit data pulled from slave to the master's database. | def commit_pull_to_db():
print("Committing pulled data")
cur = conn.cursor()
try:
for tname in TABLES:
cur.execute(f"DELETE FROM {tname};")
with open(f'{tname}.db', 'r') as f:
print(f"Copying {tname}")
cur.copy_from(f, f'"{tname}"')
con... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Commit(self):\n sql_cnxn = self.GetMasterConnection()\n try:\n sql_cnxn.commit()\n except MySQLdb.DatabaseError:\n logging.exception('Commit failed for cnxn, rolling back')\n sql_cnxn.rollback()",
"def slave_to_master():\n print(\"Shifting from slave to master\")\n stop_slave_wo... | [
"0.6980852",
"0.6679038",
"0.64713585",
"0.6355909",
"0.62791294",
"0.6135586",
"0.6130546",
"0.61136794",
"0.61062694",
"0.60972565",
"0.6095288",
"0.6005328",
"0.59964836",
"0.59951985",
"0.5989465",
"0.59722084",
"0.59344745",
"0.59253657",
"0.59253657",
"0.59253657",
"0.5... | 0.5606902 | 46 |
Reimplemented to capture the Tab key pressed/released event. | def event(self, event):
if event.type() == QEvent.ShortcutOverride and event.key() == Qt.Key_Tab:
event.accept()
return True
if event.type() == QEvent.KeyPress and event.key() == Qt.Key_Tab:
return self.keyPressEvent(event)
return super().event(event) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def OnKeyDown2(self, event):\r\n\r\n if self.GetActivePage() == -1:\r\n event.Skip()\r\n return\r\n \r\n # We can't leave tab processing to the system on Windows, tabs and keys\r\n # get eaten by the system and not processed properly if we specify both\r\n # wxT... | [
"0.6881452",
"0.6782852",
"0.6661517",
"0.66373795",
"0.6533331",
"0.6484942",
"0.64714545",
"0.6413943",
"0.62985414",
"0.62599313",
"0.6241822",
"0.62392884",
"0.62282753",
"0.61531764",
"0.61026293",
"0.609596",
"0.59973466",
"0.59498143",
"0.59262854",
"0.5887352",
"0.586... | 0.64935756 | 5 |
Uses the current cursor position, which is in a code view, and gets the corresponding instruction address that is associated to the code. Returns the start of the function if unable to calculate. | def get_src_to_inst(self) -> int:
# get the Qt document
doc: QCodeDocument = self.document()
# get the current position of the cursor
cursor = self.textCursor()
pos = cursor.position()
# get the node at the associated cursor position
current_node = doc.get_stmt... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_code(func):\n import inspect\n\n raw = \"\".join(inspect.getsource(func))\n found = re.findall(\"(k = .*)\", raw)\n\n if any(found):\n code = found[0]\n return code\n else:\n return \"\"",
"def getInstructionBefore(self, address: ghidra.... | [
"0.6299851",
"0.6007909",
"0.60040885",
"0.6001951",
"0.5926025",
"0.59078115",
"0.5856952",
"0.5770866",
"0.57665575",
"0.57530594",
"0.57365364",
"0.5735565",
"0.5707904",
"0.5673848",
"0.56713",
"0.5665861",
"0.5659602",
"0.5657597",
"0.5647901",
"0.5603577",
"0.5597595",
... | 0.7334392 | 0 |
initialize parameters using kaiming normal | def init_parameters(module: nn.Module):
for m in module.modules():
if isinstance(m, nn.Conv2d):
# todo: check if fan_out is valid
nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
elif isinstance(m, nn.BatchNorm2d):
nn.init.constant_(m.weight,... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __setup_parameters__(self):\r\n self.M=self.N+1\r\n self.u=1+self.pu\r\n self.d=1-self.pd\r\n self.qu=(math.exp((self.r-self.div)*self.dt)-self.d)/(self.u-self.d)\r\n self.qd=1-self.qu",
"def init_paramters(self):\r\n carb_bg_ratio = 5.0\r\n time_to_breakdown ... | [
"0.7051572",
"0.6925155",
"0.6915251",
"0.68529457",
"0.68099403",
"0.6714396",
"0.6687382",
"0.6675767",
"0.6673424",
"0.66504097",
"0.66460747",
"0.66280675",
"0.66103244",
"0.6576185",
"0.6574086",
"0.65717214",
"0.6559772",
"0.65528405",
"0.6546903",
"0.6539553",
"0.65352... | 0.0 | -1 |
Tests the inference method. | def test_inference(self, tmpdir, setup_task_environment):
root = str(tmpdir.mkdir("anomaly_inference_test"))
# Get task environment
setup_task_environment = deepcopy(setup_task_environment) # since fixture is mutable
task_environment = setup_task_environment.task_environment
ta... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def inference(self):\n raise NotImplementedError",
"def inference(model, data, diagnostics, seed, extra_fitting_args):\n pass",
"def inference(self, x, name):\n raise NotImplemented",
"def test_inference(VD, CD):\n \n if VD['inference_process'] == None:\n VD['terminal_output'] +... | [
"0.7798499",
"0.7028686",
"0.6684394",
"0.66657066",
"0.6625743",
"0.6539838",
"0.6301463",
"0.62897986",
"0.6276158",
"0.6228454",
"0.62056077",
"0.61593705",
"0.61272967",
"0.6122539",
"0.611181",
"0.60995996",
"0.60318434",
"0.5953834",
"0.5880599",
"0.58443904",
"0.583019... | 0.609276 | 16 |
Calculate a checksum for the given path. Will eventually use this to ensure config has changed before reloading. | def checksum(path):
with open(path, 'r') as f:
return md5(f.read()).digest() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_checksum(path: Union[Path, str]) -> str:\n path = Path(path)\n if not (path.is_file() or path.is_dir()):\n msg.fail(f\"Can't get checksum for {path}: not a file or directory\", exits=1)\n if path.is_file():\n return hashlib.md5(Path(path).read_bytes()).hexdigest()\n else:\n ... | [
"0.7271267",
"0.6893249",
"0.67964584",
"0.6699954",
"0.65897936",
"0.6586321",
"0.6519239",
"0.65081114",
"0.6485526",
"0.6472071",
"0.646679",
"0.6462213",
"0.64450413",
"0.64431435",
"0.63804424",
"0.6329311",
"0.6290257",
"0.62881494",
"0.6251396",
"0.6229306",
"0.6219351... | 0.7938589 | 0 |
Set up inotify if requested. | def _setup_inotify(self, flag):
i = None
if flag:
try:
import inotify.adapters
except ImportError:
raise AssertionError(
'cannot use inotify, package not installed')
else:
i = inotify.adapters.Inot... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def start(self):\n self._class_setup()\n\n self._inotify_fd = InotifyFileWatcher._libc.inotify_init()\n if self._inotify_fd < 0:\n error = OSError('failed call to inotify_init')\n error.errno = ctypes.get_errno()\n error.strerror = errno.errorcode[ctypes.get_errno()]\n raise error\n ... | [
"0.68859357",
"0.6521524",
"0.5825635",
"0.5661374",
"0.56051093",
"0.5601565",
"0.55341774",
"0.5521033",
"0.54301476",
"0.53801805",
"0.53308344",
"0.521609",
"0.5213829",
"0.5188312",
"0.51532716",
"0.5120239",
"0.51025105",
"0.5082971",
"0.507481",
"0.50697386",
"0.506352... | 0.7264749 | 0 |
Create watch directory if it does not exist. | def _setup_watch(self, watch):
assert not isfile(watch), 'watch dir is a file'
if pathexists(watch):
return watch
os.makedirs(watch)
if self.chown:
try:
os.chown(watch, *self.chown)
except OSError:
pass # Non-fatal
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def check_dir(self):\n\n if not os.path.isdir(self.directory):\n os.mkdir(self.directory, 755)\n if not os.path.exists(self.log_file):\n from pathlib import Path\n Path(self.log_file).touch()",
"def start_check():\n if not os.path.exists(outfancy_temp_files):\n ... | [
"0.6459634",
"0.6346766",
"0.6331183",
"0.6299552",
"0.6197254",
"0.6110146",
"0.6098661",
"0.6089687",
"0.6088672",
"0.60865545",
"0.6084467",
"0.6080845",
"0.6065921",
"0.6042916",
"0.603886",
"0.59679985",
"0.5966238",
"0.5957223",
"0.59505254",
"0.5901048",
"0.5883695",
... | 0.77630746 | 0 |
Set up for chown/chmod. | def _setup_permissions(self, chown, chmod):
if chown is not None:
if isinstance(chown, str):
user, group = chown, None
else:
try:
# Try to extract tuple.
user, group = chown
except ValueError:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setup_permissions():\n sudo('chown %s:%s -R %s' % (env.apache_user, env.apache_user, env.whole_path_symlinked))",
"def Chown(self):\n cmd = 'chmod -R 0775 %s' % self.procdir\n self.ExecCmd(cmd)",
"def set_ownership(self):\n\n os.chmod(os.path.join(\"%s\" % NetworkManager_conf_dir, s... | [
"0.7886576",
"0.7704895",
"0.7617247",
"0.75252616",
"0.7270645",
"0.72335154",
"0.7083537",
"0.70804906",
"0.6867677",
"0.6863387",
"0.6816202",
"0.67961174",
"0.6747547",
"0.67430216",
"0.6602624",
"0.65472955",
"0.6544091",
"0.64677674",
"0.6467248",
"0.6389743",
"0.637281... | 0.7632436 | 2 |
Run the service command. | def start_command(self, wait_for_config=True):
self.process = subprocess.Popen(shlex.split(self.command))
LOGGER.info(
'Command (%s) started with pid %s', self.command, self.process.pid) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _run_command_in_service(context, service, command):\n if context.docker_compose_path:\n cmd = _make_compose_command(context, 'run', '--rm', '-d', service)\n cmd.extend(command)\n else:\n raise Exception(\"not implemented\")\n\n try:\n # universal_newlines decodes output on ... | [
"0.6806571",
"0.66887987",
"0.6567109",
"0.6553368",
"0.6491652",
"0.6458441",
"0.6445283",
"0.63440955",
"0.6291305",
"0.6275552",
"0.62669",
"0.626131",
"0.6257048",
"0.62291175",
"0.622709",
"0.6215655",
"0.6206896",
"0.6186277",
"0.61826146",
"0.61619884",
"0.6153432",
... | 0.0 | -1 |
Reload configuration. If reload command is given, run that, otherwise, signal process with HUP. | def reload_command(self):
if self.reload is None:
if not self.check_command():
LOGGER.info('Command dead, restarting...')
self.start_command(wait_for_config=False)
else:
LOGGER.info('Sending HUP signal...')
self.process.sen... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def reload_config():\n subprocess.run([SUPERVISOR_CMD, \"reload\"])",
"def nginx_reload():\n log('reload nginx', yellow)\n sudo('/etc/init.d/nginx reload')",
"def reload_config(self):\n pass",
"def command_reload(interface,command,args):\n command_unload(interface,command,args)\n comman... | [
"0.75852543",
"0.6688586",
"0.6681827",
"0.66347086",
"0.633552",
"0.6311228",
"0.6310406",
"0.62902033",
"0.6279588",
"0.6202909",
"0.6199834",
"0.61551714",
"0.6126377",
"0.6089492",
"0.6079683",
"0.60628176",
"0.59531575",
"0.5931519",
"0.5927496",
"0.5915352",
"0.5904567"... | 0.8385148 | 0 |
Return False if command is dead, otherwise True. | def check_command(self):
return self.process is not None and self.process.poll() is None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_dead(self):\n if self.killer:\n if self.killer.stype == 'fire' and not (self.killer in self.pjs.fires):\n return True\n elif self.killer.stype == 'enemy' and self.timeout == 0:\n return True\n else:\n return False",
"def __is_act... | [
"0.6922289",
"0.6847067",
"0.68249875",
"0.66671854",
"0.66655314",
"0.6653957",
"0.65789324",
"0.6558258",
"0.6550506",
"0.649371",
"0.64785314",
"0.64250284",
"0.63963515",
"0.6387006",
"0.6375392",
"0.6337235",
"0.62643814",
"0.62609",
"0.6241368",
"0.6222854",
"0.62103415... | 0.69605875 | 0 |
Use polling method to enumerate files in watch dir. | def get_config_files(self):
flag, i = self.inotify
if flag:
kwargs = {}
if PY3:
kwargs['timeout_s'] = 0
filenames = set()
for event in i.event_gen(**kwargs):
if event is None:
break
f... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _watchFolder(self):\n wm = pyinotify.WatchManager()\n wm.add_watch(self.gdocs_folder, pyinotify.IN_MODIFY, rec=True)\n \n handler = EventHandler(self)\n notifier = pyinotify.Notifier(wm, handler)\n \n print 'waiting for changes . . .'\n notifier.loop()",
... | [
"0.6876409",
"0.68680036",
"0.64799684",
"0.6349804",
"0.6330774",
"0.62145215",
"0.6179047",
"0.61642784",
"0.6136405",
"0.6117507",
"0.6073316",
"0.6064468",
"0.6056099",
"0.5972339",
"0.5963462",
"0.5934348",
"0.59193623",
"0.59006125",
"0.5864853",
"0.5843844",
"0.5831716... | 0.6089402 | 10 |
Get unique list of new config files in watch dir. | def get_config(self):
config = set()
while True:
filenames = self.get_config_files()
for fn in filenames:
if fn not in self.watch_names:
filenames.remove(fn)
if fn in config:
filenames.remove(fn)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_config_files(self):\n flag, i = self.inotify\n\n if flag:\n kwargs = {}\n\n if PY3:\n kwargs['timeout_s'] = 0\n\n filenames = set()\n\n for event in i.event_gen(**kwargs):\n if event is None:\n break\... | [
"0.7831209",
"0.70418906",
"0.66463995",
"0.6577422",
"0.64742094",
"0.64292943",
"0.64021975",
"0.6402068",
"0.63111544",
"0.62958807",
"0.6260233",
"0.61890477",
"0.61561424",
"0.61066765",
"0.610564",
"0.6097907",
"0.6075739",
"0.6075056",
"0.6053437",
"0.6035494",
"0.6028... | 0.7109554 | 1 |
Kill the running command. | def kill(self):
if self.process is not None:
LOGGER.info('Killing command...')
self.process.kill()
self.process = None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def kill(self):\n\n self.proc.kill()",
"def kill(self):\n self._process.kill()",
"def kill(self):\n self._stop_proc(signal.SIGKILL)",
"def kill(self):\n self._update()\n if self.running_mode == \"local\":\n for process in self.processes:\n try:\n ... | [
"0.7861475",
"0.7555022",
"0.749188",
"0.7406674",
"0.72241443",
"0.7057569",
"0.7053252",
"0.7020611",
"0.7016701",
"0.69516635",
"0.693628",
"0.6888209",
"0.6873801",
"0.6854114",
"0.6798234",
"0.6792874",
"0.67909163",
"0.6775448",
"0.674491",
"0.6723775",
"0.6702169",
"... | 0.8239272 | 0 |
Run test command to verify configuration. | def test_command(self, quiet=True):
# If there is no test command, assume the config is good to go.
if self.test is None:
return True
# Attempt parse.
kwargs = {}
if quiet:
kwargs['stdout'] = DEVNULL
kwargs['stderr'] = subprocess.STDOUT
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Checktest(self, expectedoutput):\n\n if expectedoutput == 0:\n result = self.runner.invoke(yoda.cli, [\"setup\", \"check\"])\n self.assertEqual(result.exit_code, 0)\n self.assertIn(\"The configuration file does not exist.\", result.output)\n return\n\n ... | [
"0.69138324",
"0.67915976",
"0.6790115",
"0.67689073",
"0.6737845",
"0.6722288",
"0.6666319",
"0.66587526",
"0.65559405",
"0.6525426",
"0.651796",
"0.65171564",
"0.64026606",
"0.6394368",
"0.6387093",
"0.6379195",
"0.63411385",
"0.6338479",
"0.630961",
"0.62860626",
"0.621526... | 0.6250256 | 20 |
Backs up entire configuration. | def backup_config(self):
prev_config = set()
for src in self.config:
dst = '%s.prev' % src
LOGGER.debug('Backing up %s to %s', src, dst)
try:
shutil.copy(src, dst)
except IOError as e:
if e.errno != errno.ENOENT:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def backup(config_file, bakfile):\n return _backup_config(config_file, bakfile)",
"def backup(ctx, project, origin, force):\n\n if not check_main_conf(ctx):\n return\n\n if origin is not None and project is None:\n click.echo(\"--project option is required when --origin is set.\")\n ... | [
"0.6370239",
"0.62242675",
"0.61583614",
"0.61377156",
"0.6079129",
"0.60359734",
"0.59865093",
"0.59671223",
"0.59083843",
"0.5764068",
"0.5725047",
"0.5714281",
"0.56883514",
"0.56292564",
"0.5621002",
"0.5616206",
"0.5596354",
"0.5594662",
"0.55940187",
"0.5514033",
"0.549... | 0.6756827 | 0 |
Remove backup once command is restarted. | def remove_config(self, config):
for fn in config:
try:
os.remove(fn)
LOGGER.debug('Removed backup: %s', fn)
except IOError as e:
if e.errno != errno.ENOENT:
LOGGER.warning('Could not remove backup: %s', fn) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __removeBackup(self):\n pass #FIXME!!",
"def delete_old_backup(self):\n print \"### Info ### Delete redundant backups\"\n for i in range(len(self.date_list)-20):\n os.remove(os.path.abspath(self.backup_path + U'/voc2brain_backup_' + str(self.date_list[0])+ \".sdb3\") )",
"de... | [
"0.8196065",
"0.70776635",
"0.6619657",
"0.63696575",
"0.62427235",
"0.61607236",
"0.613132",
"0.61143297",
"0.61006206",
"0.60654944",
"0.6063608",
"0.60433877",
"0.6026956",
"0.59964967",
"0.5993778",
"0.59595126",
"0.5955549",
"0.5950114",
"0.58985144",
"0.5865423",
"0.585... | 0.5485173 | 58 |
Restores a previous config backup. | def restore_config(self, config):
for src in config:
# Remove .prev
dst, _ = splitext(src)
LOGGER.debug('Restoring %s from %s', dst, src)
shutil.move(src, dst) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __restoreBackup(self):\n pass #FIXME!!!",
"def restore_config(self):\n self._clear_previous_windows_assigment()\n self._restart_i3_config()",
"def restore_backup():\n\n # restore vim configuration folder\n if exists('.vim-bkp'):\n print(green('Restoring your vim configurat... | [
"0.72900516",
"0.7256316",
"0.7031564",
"0.68569666",
"0.67252886",
"0.6492015",
"0.6481564",
"0.64403677",
"0.64377254",
"0.63916713",
"0.6362085",
"0.6353648",
"0.6302588",
"0.62942183",
"0.6231615",
"0.62304366",
"0.618073",
"0.6173418",
"0.6165256",
"0.6148223",
"0.608969... | 0.68605244 | 3 |
Copy new configuration to location service expects. | def install_config(self, config):
for fn in config:
dst = [p for p in self.config if basename(p) == fn][0]
src = pathjoin(self.watch, fn)
try:
os.makedirs(dirname(dst))
except OSError as e:
if e.errno != errno.EEXIST:
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _prepare(self):\n logging.info('-> copy configuration...')\n path_cofig = self.params['path_config_bUnwarpJ']\n shutil.copy(path_cofig, os.path.join(self.params['path_exp'],\n os.path.basename(path_cofig)))\n if 'path_config_IJ_SIFT' in se... | [
"0.66751164",
"0.6538778",
"0.6319601",
"0.6304055",
"0.6287822",
"0.6230367",
"0.62281555",
"0.6134705",
"0.6039623",
"0.6001801",
"0.59539455",
"0.59479195",
"0.5938517",
"0.5936677",
"0.5883111",
"0.5872014",
"0.5860854",
"0.5835609",
"0.58065426",
"0.5762701",
"0.5741781"... | 0.5214433 | 95 |
Backup old config, write new config, test config, HUP or restore. | def test_and_swap(self, config):
LOGGER.info('Attempting to apply new configuration')
backup = self.backup_config()
# We have backed up ALL config files (not just the ones we might
# replace). If any error occurs from here out, we will need to restore
# our config, so we will use... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _backup_config(config_file, bak_path=None):\n try:\n if not bak_path:\n bak_path = config_file+\".bak\"\n with open(config_file, 'r') as oldfile, open(bak_path, 'w') as bakfile:\n tmp = oldfile.read(1024)\n while tmp:\n bakfile.write(tmp)\n ... | [
"0.7156795",
"0.7003359",
"0.67606544",
"0.6459555",
"0.64326864",
"0.63440835",
"0.63262016",
"0.63146156",
"0.62513983",
"0.6244165",
"0.6195551",
"0.61006075",
"0.60527635",
"0.6048218",
"0.60470015",
"0.60405976",
"0.6031093",
"0.59871054",
"0.5954373",
"0.59194183",
"0.5... | 0.72788405 | 0 |
Plot and save histograms from predicted steerings and real steerings. Arguments | def make_and_save_histogramsX(pred_steerings, real_steerings,
img_name = "histogramsX.png"):
pred_steerings = np.array(pred_steerings)
real_steerings = np.array(real_steerings)
max_h = np.maximum(np.max(pred_steerings), np.max(real_steerings))
min_h = np.minimum(np.min(pred_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_and_save_histogramsY(pred_steerings, real_steerings,\n img_name = \"histogramsY.png\"):\n pred_steerings = np.array(pred_steerings)\n real_steerings = np.array(real_steerings)\n max_h = np.maximum(np.max(pred_steerings), np.max(real_steerings))\n min_h = np.minimum(... | [
"0.76754117",
"0.64281666",
"0.6419849",
"0.63231015",
"0.6262315",
"0.62221205",
"0.6151655",
"0.6125331",
"0.6123557",
"0.61125845",
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"0.6062547",
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"0.6034784",
"0.6033427",
"0.60138935",
"0.6013693",
"0.6010012",
"0.59823984",
"0.59726... | 0.7740116 | 0 |
Plot and save histograms from predicted steerings and real steerings. Arguments | def make_and_save_histogramsY(pred_steerings, real_steerings,
img_name = "histogramsY.png"):
pred_steerings = np.array(pred_steerings)
real_steerings = np.array(real_steerings)
max_h = np.maximum(np.max(pred_steerings), np.max(real_steerings))
min_h = np.minimum(np.min(pred_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_and_save_histogramsX(pred_steerings, real_steerings,\n img_name = \"histogramsX.png\"):\n pred_steerings = np.array(pred_steerings)\n real_steerings = np.array(real_steerings)\n max_h = np.maximum(np.max(pred_steerings), np.max(real_steerings))\n min_h = np.minimum(... | [
"0.7740603",
"0.6428022",
"0.6419536",
"0.6322531",
"0.62623787",
"0.62226415",
"0.61514246",
"0.61257786",
"0.6123551",
"0.6112254",
"0.6079733",
"0.6064892",
"0.6062117",
"0.60601425",
"0.6035143",
"0.6033051",
"0.601378",
"0.6013595",
"0.6009719",
"0.5982897",
"0.59727293"... | 0.7675895 | 1 |
Plot and save confusion matrix computed from predicted and real labels. Arguments | def plot_confusion_matrix(real_labels, pred_prob, classes,
normalize=False,
img_name="confusion.png"):
real_labels = np.array(real_labels)
# Binarize predicted probabilities
pred_prob = np.array(pred_prob)
pred_labels = np.zeros_like(pred_prob)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def plot_confusion_matrix(self, y_true, y_pred, title=None):\r\n\r\n if not title:\r\n title = 'confusion matrix'\r\n\r\n # Compute confusion matrix\r\n\r\n y_pred = np.array(y_pred)\r\n y_true = np.array(y_true)\r\n cm = confusion_matrix(y_true, y_pred)\r\n # O... | [
"0.7909803",
"0.77706945",
"0.7693289",
"0.7669506",
"0.7644297",
"0.7616977",
"0.757757",
"0.75686",
"0.7555622",
"0.7483602",
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"0.7465456",
"0.74556404",
"0.7446722",
"0.74444157",
"0.7443814",
"0.74419767",
... | 0.7841449 | 1 |
Set up Tasmota sensor dynamically through discovery. | async def async_setup_entry(hass, config_entry, async_add_entities):
async def async_discover_sensor(tasmota_entity, discovery_hash):
"""Discover and add a Tasmota sensor."""
async_add_entities(
[
TasmotaSensor(
tasmota_entity=tasmota_entity, discover... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def async_discover_sensor(tasmota_entity, discovery_hash):\n async_add_entities(\n [\n TasmotaSensor(\n tasmota_entity=tasmota_entity, discovery_hash=discovery_hash\n )\n ]\n )",
"def setup_sensors(self):\n self._ta... | [
"0.6551506",
"0.64838266",
"0.64127916",
"0.63373846",
"0.6302272",
"0.62259805",
"0.6224144",
"0.61740553",
"0.61011136",
"0.6077729",
"0.60729074",
"0.6011457",
"0.5998973",
"0.5998924",
"0.599695",
"0.5978081",
"0.59712714",
"0.59689814",
"0.5960322",
"0.5929455",
"0.59252... | 0.5853148 | 24 |
Discover and add a Tasmota sensor. | async def async_discover_sensor(tasmota_entity, discovery_hash):
async_add_entities(
[
TasmotaSensor(
tasmota_entity=tasmota_entity, discovery_hash=discovery_hash
)
]
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def async_add_binary_sensor(mac):\n if USB_MOTION_ID in api_stick.devices[mac].features:\n _LOGGER.debug(\"Add binary_sensors for %s\", mac)\n async_add_entities([USBBinarySensor(api_stick.devices[mac])])\n\n # Register services\n platform.async_register_ent... | [
"0.6059688",
"0.583049",
"0.5694654",
"0.5584414",
"0.5579093",
"0.55689627",
"0.55304766",
"0.5517644",
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"0.5372278",
"0.5371746",
"0.5358791",
"0.53568757",
"0.53443986",
"0.5335553",
"0.5331908"... | 0.65760076 | 0 |
Initialize the Tasmota sensor. | def __init__(self, **kwds):
self._state = None
super().__init__(
discovery_update=self.discovery_update,
**kwds,
) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self):\n\n super().__init__()\n\n self.active = True\n self.driver = Driver.instance()\n self.sensor_manager = SensorManager.instance()\n\n self.pwm = Adafruit_PCA9685.PCA9685(address=0x40, busnum=1) # create PCA9685-object at I2C-port\n self.pwm.set_pwm_freq... | [
"0.61697245",
"0.5928329",
"0.5887117",
"0.5875876",
"0.586315",
"0.5852638",
"0.5817024",
"0.57665086",
"0.576379",
"0.5753676",
"0.57419896",
"0.5735377",
"0.5708823",
"0.5682858",
"0.5679623",
"0.56617826",
"0.5624354",
"0.5596242",
"0.55879885",
"0.5565041",
"0.5562199",
... | 0.0 | -1 |
Return the device class of the sensor. | def device_class(self) -> Optional[str]:
class_or_icon = SENSOR_DEVICE_CLASS_ICON_MAP.get(
self._tasmota_entity.quantity, {}
)
return class_or_icon.get(DEVICE_CLASS) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def device_class(self):\n return self.sensor_type[\"class\"]",
"def device_class(self):\n return SENSOR_TYPES[self.sensor][3].get(\"device_class\")",
"def device_class(self):\n return self._sensor_type",
"def device_class(self):\r\n return self._sensor_cfg[3]",
"def device_class... | [
"0.93628424",
"0.92430294",
"0.9240069",
"0.9161452",
"0.9161452",
"0.9156968",
"0.90412056",
"0.90412056",
"0.8956785",
"0.89529496",
"0.8950599",
"0.8919914",
"0.871994",
"0.8717259",
"0.87069035",
"0.8660478",
"0.8652474",
"0.83961546",
"0.83828783",
"0.8380708",
"0.838070... | 0.81339943 | 31 |
Return if the entity should be enabled when first added to the entity registry. | def entity_registry_enabled_default(self) -> bool:
# Hide status sensors to not overwhelm users
if self._tasmota_entity.quantity in status_sensor.SENSORS:
return False
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _enabled_entity_exists(self) -> bool:\n return self.entity_exists(self._enabled_toggle_entity_id)",
"def entity_registry_enabled_default(self) -> bool:\n return self._enabled_default",
"def entity_registry_enabled_default(self) -> bool:\n return False",
"def entity_registry_enabled_defau... | [
"0.76484686",
"0.7445516",
"0.7369543",
"0.7279766",
"0.7243998",
"0.7243998",
"0.72242576",
"0.702323",
"0.68542576",
"0.6784123",
"0.67786515",
"0.66620255",
"0.6639556",
"0.6639556",
"0.6639556",
"0.6639556",
"0.6639556",
"0.6639556",
"0.66098607",
"0.65822154",
"0.6575364... | 0.7130893 | 7 |
Return the state of the entity. | def state(self):
return self._state | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def state(self):\n return self.get_state()",
"def state(self):\n result = self.getResult()\n return result.state",
"def getState(self) :\n return self.state",
"def getState(self):\n return self.state",
"def getState(self):\n return self.state",
"def getState(self... | [
"0.770336",
"0.7654755",
"0.76498735",
"0.7620778",
"0.7620778",
"0.7620778",
"0.75572854",
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"0.73821914",
"0.73821914",
"0.73821914",
"0.73821914",
"0.73806906",
"0.735... | 0.727765 | 94 |
Return the unit this state is expressed in. | def unit_of_measurement(self):
return self._tasmota_entity.unit | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_unit(self):\n return self.unit",
"def unit(self):\n return self._unit",
"def unit(self):\n return self._unit",
"def unit(self):\n return self._unit",
"def unit(self):\n return self.__unit",
"def unit(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"... | [
"0.8381375",
"0.82579356",
"0.82013446",
"0.82013446",
"0.81742126",
"0.791395",
"0.7801508",
"0.7801508",
"0.7801508",
"0.7801508",
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"0.7801508",
"0.7801508",
"0.7801508",
"0.7801508",
"0.7801508",
"0.7801508",
... | 0.8035094 | 5 |
Set up the Garmin Connect component. | async def async_setup(hass: HomeAssistant, config: dict):
hass.data[DOMAIN] = {}
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def connect(self):\n pass",
"def connect(self):\n pass",
"def connect(self):\n pass",
"def connect(self):\n pass",
"def connect(self):\n pass",
"def connect(self):\n pass",
"def connect(self):\n pass",
"def connect(self):\n pass",
"def connect... | [
"0.62827325",
"0.62827325",
"0.62827325",
"0.62827325",
"0.62827325",
"0.62827325",
"0.62827325",
"0.62827325",
"0.62815505",
"0.61928016",
"0.61755365",
"0.6139352",
"0.6137068",
"0.61368144",
"0.6065569",
"0.60075444",
"0.5984593",
"0.59311897",
"0.59311897",
"0.5917158",
"... | 0.0 | -1 |
Set up Garmin Connect from a config entry. | async def async_setup_entry(hass: HomeAssistant, entry: ConfigEntry):
username = entry.data[CONF_USERNAME]
password = entry.data[CONF_PASSWORD]
garmin_client = Garmin(username, password)
try:
await hass.async_add_executor_job(garmin_client.login)
except (
GarminConnectAuthenticatio... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_config(config_name, host, port, core=''):\n global CONFIGS\n CONFIGS[config_name] = {'host': host, 'port': port, 'core': core}",
"def setup():\n\tglobal config_parser, config_file\n\tglobal prefix\n\n\tif os.path.islink(sys.argv[0]):\n\t\tlink = os.readlink(sys.argv[0])\n\n\t\tif not os.path.isabs(... | [
"0.62775207",
"0.60732806",
"0.5851702",
"0.58259803",
"0.5785242",
"0.57221854",
"0.57136893",
"0.56654847",
"0.56587076",
"0.56587076",
"0.56514394",
"0.5620723",
"0.55982435",
"0.5576343",
"0.55624145",
"0.5553576",
"0.55496615",
"0.554902",
"0.554902",
"0.5542576",
"0.552... | 0.5439701 | 30 |
Unload a config entry. | async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry):
unload_ok = all(
await asyncio.gather(
*[
hass.config_entries.async_forward_entry_unload(entry, component)
for component in PLATFORMS
]
)
)
if unload_ok:
has... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"async def async_unload_entry(hass, config_entry):\n unload_ok = await hass.config_entries.async_forward_entry_unload(\n config_entry, \"climate\"\n )\n return unload_ok",
"async def async_unload_entry(hass: HomeAssistant, entry: ConfigEntry) -> bool:\n hass.data.pop(DOMAIN)\n return True",
... | [
"0.697284",
"0.6888074",
"0.6779855",
"0.6747459",
"0.6689002",
"0.6657831",
"0.66162205",
"0.6603433",
"0.65925974",
"0.65595686",
"0.65411645",
"0.6507643",
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"0.6507643",
"0.64977276",
"0.64931643",
"0.6486601",
"0.6486601",
"0.6486601",
"0.6486601"... | 0.6459733 | 28 |
Update data via library. | async def async_update(self):
today = date.today()
try:
self.data = await self.hass.async_add_executor_job(
self.client.get_stats_and_body, today.isoformat()
)
except (
GarminConnectAuthenticationError,
GarminConnectTooManyRequests... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def update_data():\n pass",
"def update(self, data):\n pass",
"def update(self, data):\n pass",
"def update(self, data):\n pass",
"def update(self, data):\n pass",
"def update(self, data):\n self.data.update(data)",
"def update(self, data):\n return ... | [
"0.8435785",
"0.8008672",
"0.8008672",
"0.8008672",
"0.8008672",
"0.7589883",
"0.7447164",
"0.7291235",
"0.7291235",
"0.72886306",
"0.72539234",
"0.7127528",
"0.71165633",
"0.7108259",
"0.7090543",
"0.7049341",
"0.7018547",
"0.7013633",
"0.69404083",
"0.69404083",
"0.69404083... | 0.0 | -1 |
Installs the OpenMPI package on the VM. | def _Install(vm):
vm.Install('build_tools')
vm.Install('wget')
vm.RemoteCommand('wget %s -P %s' % (MPI_URL, INSTALL_DIR))
vm.RemoteCommand('cd %s && tar xvfz %s' % (INSTALL_DIR, MPI_TAR))
make_jobs = vm.NumCpusForBenchmark()
shared_lib_command = ('--enable-shared' if FLAGS.openmpi_enable_shared
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def AptInstall(vm):\n vm.RobustRemoteCommand('sudo apt-get {}'.format(REMOVE_MPI_CMD))\n _Install(vm)",
"def YumInstall(vm):\n vm.RobustRemoteCommand('sudo yum {}'.format(REMOVE_MPI_CMD))\n _Install(vm)",
"def install():\n PackCommandExecutor().pack()\n InstallCommandExecutor().install()",
"def ins... | [
"0.749848",
"0.6820002",
"0.6406495",
"0.6319433",
"0.62312424",
"0.61590135",
"0.61590135",
"0.6028888",
"0.59898764",
"0.5981365",
"0.5926291",
"0.59055406",
"0.5884631",
"0.58507264",
"0.5765704",
"0.5713537",
"0.57048243",
"0.5699972",
"0.5699972",
"0.5667024",
"0.5660338... | 0.80011517 | 0 |
Installs the OpenMPI package on the VM. | def YumInstall(vm):
vm.RobustRemoteCommand('sudo yum {}'.format(REMOVE_MPI_CMD))
_Install(vm) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _Install(vm):\n vm.Install('build_tools')\n vm.Install('wget')\n vm.RemoteCommand('wget %s -P %s' % (MPI_URL, INSTALL_DIR))\n vm.RemoteCommand('cd %s && tar xvfz %s' % (INSTALL_DIR, MPI_TAR))\n make_jobs = vm.NumCpusForBenchmark()\n shared_lib_command = ('--enable-shared' if FLAGS.openmpi_enable_shared\n... | [
"0.80011517",
"0.749848",
"0.6406495",
"0.6319433",
"0.62312424",
"0.61590135",
"0.61590135",
"0.6028888",
"0.59898764",
"0.5981365",
"0.5926291",
"0.59055406",
"0.5884631",
"0.58507264",
"0.5765704",
"0.5713537",
"0.57048243",
"0.5699972",
"0.5699972",
"0.5667024",
"0.566033... | 0.6820002 | 2 |
Installs the OpenMPI package on the VM. | def AptInstall(vm):
vm.RobustRemoteCommand('sudo apt-get {}'.format(REMOVE_MPI_CMD))
_Install(vm) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _Install(vm):\n vm.Install('build_tools')\n vm.Install('wget')\n vm.RemoteCommand('wget %s -P %s' % (MPI_URL, INSTALL_DIR))\n vm.RemoteCommand('cd %s && tar xvfz %s' % (INSTALL_DIR, MPI_TAR))\n make_jobs = vm.NumCpusForBenchmark()\n shared_lib_command = ('--enable-shared' if FLAGS.openmpi_enable_shared\n... | [
"0.80011517",
"0.6820002",
"0.6406495",
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"0.5713537",
"0.57048243",
"0.5699972",
"0.5699972",
"0.5667024",
"0.56603... | 0.749848 | 1 |
Uninstalls the OpenMPI package on the VM. | def _Uninstall(vm):
vm.RemoteCommand('cd {0} && sudo make uninstall'.format(MPI_DIR)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def AptUninstall(vm):\n remove_str = 'sudo apt-get --purge autoremove -y '\n for package in APT_PACKAGES:\n vm.RemoteCommand(remove_str + package)",
"def AptUninstall(vm):\n _Uninstall(vm)",
"def YumUninstall(vm):\n _Uninstall(vm)",
"def _unprovision_node(self, conn):\n conn.run(f\"rm -rf {EXPO... | [
"0.6643343",
"0.6554691",
"0.6437639",
"0.61634016",
"0.61421573",
"0.6033786",
"0.6024719",
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"0.59412205",
"0.59231645",
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"0.57771873",
"0.57449394",
"0.5722418",
"0.57108957",
"0.5706674",
"0.56761074",
"0.56503... | 0.8364465 | 0 |
Uninstalls the OpenMPI package on the VM. | def YumUninstall(vm):
_Uninstall(vm) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _Uninstall(vm):\n vm.RemoteCommand('cd {0} && sudo make uninstall'.format(MPI_DIR))",
"def AptUninstall(vm):\n remove_str = 'sudo apt-get --purge autoremove -y '\n for package in APT_PACKAGES:\n vm.RemoteCommand(remove_str + package)",
"def AptUninstall(vm):\n _Uninstall(vm)",
"def _unprovision_no... | [
"0.8364465",
"0.6643343",
"0.6554691",
"0.61634016",
"0.61421573",
"0.6033786",
"0.6024719",
"0.5982157",
"0.59412205",
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"0.5779653",
"0.57771873",
"0.57449394",
"0.5722418",
"0.57108957",
"0.5706674",
"0.56761074",
"0.56503... | 0.6437639 | 3 |
Uninstalls the OpenMPI package on the VM. | def AptUninstall(vm):
_Uninstall(vm) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _Uninstall(vm):\n vm.RemoteCommand('cd {0} && sudo make uninstall'.format(MPI_DIR))",
"def AptUninstall(vm):\n remove_str = 'sudo apt-get --purge autoremove -y '\n for package in APT_PACKAGES:\n vm.RemoteCommand(remove_str + package)",
"def YumUninstall(vm):\n _Uninstall(vm)",
"def _unprovision_no... | [
"0.8364465",
"0.6643343",
"0.6437639",
"0.61634016",
"0.61421573",
"0.6033786",
"0.6024719",
"0.5982157",
"0.59412205",
"0.59231645",
"0.5891756",
"0.5881228",
"0.5796456",
"0.5779653",
"0.57771873",
"0.57449394",
"0.5722418",
"0.57108957",
"0.5706674",
"0.56761074",
"0.56503... | 0.6554691 | 2 |
Sample from Gumbel(0, 1) | def sample_gumbel(shape, eps=1e-10):
U = torch.rand(shape).float()
return - torch.log(eps - torch.log(U + eps)) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sample(self):\n return self._root.sample()",
"def _sample_gumbel(self, shape, eps=1e-20):\r\n U = tf.random_uniform(shape, minval=0, maxval=1)\r\n return -tf.log(-tf.log(U + eps) + eps)",
"def _sample_gumbel(shape, eps=1e-10, out=None):\n if out is None:\n U = torch.rand(shape)\n... | [
"0.7220574",
"0.716382",
"0.71507114",
"0.70995146",
"0.699274",
"0.6973968",
"0.6961668",
"0.6939623",
"0.69043535",
"0.69043535",
"0.68841726",
"0.6842815",
"0.68167746",
"0.6810973",
"0.6809102",
"0.6749228",
"0.6749228",
"0.670747",
"0.6694305",
"0.6573771",
"0.65735567",... | 0.712813 | 3 |
Draw a sample from the GumbelSoftmax distribution | def gumbel_softmax_sample(logits, tau=1, eps=1e-10):
gumbel_noise = sample_gumbel(logits.size(), eps=eps).to(logits.device)
y = logits + gumbel_noise
return F.softmax(y / tau, dim=-1) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __call__(self,logits):\n \n #sample from Gumbel(0, 1)\n uniform = self._srng.uniform(logits.shape,low=0,high=1)\n gumbel = -T.log(-T.log(uniform + self.eps) + self.eps)\n \n #draw a sample from the Gumbel-Softmax distribution\n return T.nnet.softmax((log... | [
"0.6941609",
"0.6940321",
"0.67074233",
"0.67074233",
"0.6654661",
"0.6653647",
"0.66407585",
"0.66212577",
"0.6611909",
"0.66037244",
"0.6586376",
"0.6510714",
"0.64653856",
"0.64653856",
"0.6389543",
"0.6238159",
"0.62353337",
"0.62065417",
"0.620225",
"0.61525905",
"0.6108... | 0.5875712 | 28 |
Sample from the GumbelSoftmax distribution and optionally discretize. | def gumbel_softmax(logits, tau=1, hard=False, eps=1e-10):
y_soft = gumbel_softmax_sample(logits, tau=tau, eps=eps)
if hard:
shape = logits.size()
_, k = y_soft.data.max(-1)
# this bit is based on
# https://discuss.pytorch.org/t/stop-gradients-for-st-gumbel-softmax/530/5
y... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __call__(self,logits):\n \n #sample from Gumbel(0, 1)\n uniform = self._srng.uniform(logits.shape,low=0,high=1)\n gumbel = -T.log(-T.log(uniform + self.eps) + self.eps)\n \n #draw a sample from the Gumbel-Softmax distribution\n return T.nnet.softmax((log... | [
"0.6209665",
"0.6097411",
"0.6038015",
"0.6031522",
"0.6009968",
"0.60037225",
"0.5969186",
"0.59546846",
"0.594529",
"0.59424144",
"0.59238946",
"0.5917662",
"0.5917157",
"0.58992356",
"0.58821446",
"0.58690953",
"0.5866002",
"0.5855132",
"0.5850308",
"0.58380175",
"0.582960... | 0.0 | -1 |
This function opens the database.txt file and checks all the entries and returns a line in the database.txt file | def getbook():
#Opens the database file to read the lines
with open("database.txt", "r") as f:
#Iterates through each line and splits the line into individual strings
for line in f:
s=line.strip()
string=s.split(":")
return(string) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read_database(self):\n # open the database\n f = open('KISS_LINES','r')\n # make a list which will contain lines\n tlc = []\n for row in f:\n tlc.append(f.readline())\n f.close()\n\n return tlc",
"def lookForDB():\n done = False\n msg = \"\"\n... | [
"0.61832035",
"0.61019087",
"0.5959006",
"0.5931096",
"0.5930615",
"0.5808133",
"0.57629114",
"0.5742603",
"0.5694034",
"0.56101996",
"0.5608124",
"0.5526544",
"0.5519519",
"0.5513351",
"0.5489417",
"0.54727405",
"0.54715866",
"0.54519093",
"0.5449876",
"0.5423103",
"0.541830... | 0.6053122 | 2 |
This method provides an ability to set order book's deep on the fly. If some of deep's parameters is <0 (bid_count or ask_count) then method raise the custom ChangeOrderBookDeepError exception. | def set_deep(self, deep: Deep) -> None:
def is_deep_invalid(var: Deep):
return not isinstance(var, Deep) \
or False in [str(value).isdigit() for value in deep.__dict__.values()] \
or deep.bid_count < 0 \
or deep.ask_count < 0
# Exit ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_overflow_bids_market_default_depth(new_order_book: Callable[[], OrderBook]) -> NoReturn:\n book = new_order_book\n\n for _ in range(book.depth):\n book.add_offer('bids', 1, 1)\n\n assert book.depth == len(book.bids)\n assert not book.asks\n\n # try to put 21th lot into bids\n with... | [
"0.5391954",
"0.52650684",
"0.5231182",
"0.5148186",
"0.46605176",
"0.46045893",
"0.4553652",
"0.44586703",
"0.43845412",
"0.43609735",
"0.4305438",
"0.42446724",
"0.42142078",
"0.40942338",
"0.40583956",
"0.40488294",
"0.40381512",
"0.4022892",
"0.4010043",
"0.40016043",
"0.... | 0.79812324 | 0 |
This method provide an ability to place an order in order book. After each addition of order the list will be resorted by price (first orders contains the highest price) | def place_order(self, order: Order) -> None:
if order.id in [order.id for order in self.orders]:
raise OrderAlreadyCreatedError(order)
if not order.symbol.is_enabled:
raise SymbolIsNotEnabledError(order.symbol)
t = Thread(target=self.__place_order, args=(order,))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __sort_orders_by_price(self):\n self.orders = sorted(self.orders, key=lambda o: o.price, reverse=True)",
"def order(self, order):\n\n #print(\"Evaluating order: \", order)\n if self.security != order.secid:\n raise (\"Cannot place order for security \"\n \"%s... | [
"0.72955734",
"0.72195446",
"0.71405244",
"0.68157446",
"0.68157446",
"0.66305166",
"0.6570422",
"0.64215416",
"0.6358998",
"0.6337733",
"0.62889314",
"0.6281809",
"0.6275868",
"0.6248093",
"0.62321734",
"0.6133264",
"0.6128235",
"0.61075634",
"0.60340667",
"0.6027881",
"0.59... | 0.6340491 | 9 |
Private method that provide an ability to sort the orders by price | def __sort_orders_by_price(self):
self.orders = sorted(self.orders, key=lambda o: o.price, reverse=True) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_ordering_by_price_desc(self):\n request = self.factory.get('/api/v1/cars', {'distance': 10000,\n 'ordering': '-price'})\n response = CarAdViewSet.as_view({'get': 'list'})(request)\n self.assertEqual(response.status_code, HTTPStatus.OK... | [
"0.6997947",
"0.6924603",
"0.68009967",
"0.64891934",
"0.64143217",
"0.6405557",
"0.63602364",
"0.62634486",
"0.6196882",
"0.61302906",
"0.60694",
"0.6041694",
"0.5944023",
"0.5943299",
"0.5924566",
"0.59217286",
"0.5914415",
"0.59045845",
"0.58919334",
"0.58767736",
"0.58767... | 0.8428332 | 0 |
This method provide an ability to get order from order book by order action (sell or buy). By other words you can get asks or bids here. | def get_orders_by_action(self, action: OrderAction, count: int = None) -> list:
if not isinstance(count, int) and count is not None:
return list()
return [order for order in self.orders if order.action == action][:count] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def order_book_fetch(self, symbol):\n orderbook = self.orderbooks[symbol]\n asks = [[float(price), float(stats[0]) * float(stats[1])] for price, stats in orderbook['asks'].items()]\n bids = [[float(price), float(stats[0]) * float(stats[1])] for price, stats in orderbook['bids'].items()]\n ... | [
"0.71501344",
"0.6836726",
"0.6609372",
"0.65721977",
"0.63465905",
"0.6233696",
"0.6085227",
"0.6083367",
"0.60727364",
"0.6054158",
"0.60227066",
"0.6011243",
"0.5949031",
"0.5942736",
"0.59371984",
"0.593053",
"0.5894108",
"0.58863455",
"0.58636063",
"0.58327985",
"0.58307... | 0.58196706 | 21 |
This method provide an ability to find order by id and reject it. | def reject_order(self, order: Order) -> None:
order = self.get_order_by_id(order.id)
order.status = OrderStatus.REJECT | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _on_order_not_found(self, msg):\r\n parts = msg[\"id\"].split(\":\")\r\n oid = parts[1]\r\n self.debug(\"### got 'Order not found' for\", oid)\r\n # we are now going to fake a user_order message (the one we\r\n # obviously missed earlier) that will have the effect of\r\n ... | [
"0.6331195",
"0.6186556",
"0.6181075",
"0.6084242",
"0.5875732",
"0.57537323",
"0.5748262",
"0.5568031",
"0.5513399",
"0.5510577",
"0.5493943",
"0.54261667",
"0.54258156",
"0.5360014",
"0.52910525",
"0.5274176",
"0.52361274",
"0.51995444",
"0.5193858",
"0.51862836",
"0.516938... | 0.65955037 | 0 |
This method provide an ability to fill order in order book. This action means that order is completed. | def fill_order(self, order: Order) -> None:
order = self.get_order_by_id(order.id)
order.status = OrderStatus.FILL | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def complete_order(order):\n enroll_user_in_order_items(order)\n\n # If this order included assigned coupons, update them to indicate that they're redeemed\n order_coupon_ids = order.couponredemption_set.values_list(\n \"coupon_version__coupon__id\", flat=True\n )\n if order_coupon_ids:\n ... | [
"0.69658357",
"0.6763817",
"0.6571123",
"0.6434398",
"0.642819",
"0.637576",
"0.63689506",
"0.6323911",
"0.6295991",
"0.6225115",
"0.6218789",
"0.6211016",
"0.619821",
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"0.61738944",
"0.61684597",
"0.61589706",
"0.6155346",
"0.61527157",
"0.61496073",
"0.61088544... | 0.72761214 | 0 |
This method provide an ability to find and return order by using order id. | def get_order_by_id(self, order_id: uuid4) -> Order:
return next(filter(lambda order: order.id == order_id, self.orders), None) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_order(self, order_id):\n for o in self.order_lst:\n if o.get_orderId() == order_id:\n return o",
"def get_specific_order(self,order_id):\n self.query = \"SELECT * FROM orders WHERE order_id=%s\"\n self.input = (order_id,) #tuple to support indexing\n ... | [
"0.7514056",
"0.721555",
"0.70594895",
"0.7021259",
"0.69872725",
"0.6922816",
"0.69152623",
"0.68144035",
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"0.64718544",
"0.64614034",
"0.64035887",
"0.6351011",
"0.63160884",
"0.6310548",
"0.630651... | 0.70215946 | 3 |
This method provide an ability to get a market data snapshot. For example it can be helpful when you need to print order book or sent it to someone. | def get_market_data(self) -> dict:
return MarketData(asks=self.get_orders_by_action(OrderAction.SELL, self.deep.ask_count),
bids=self.get_orders_by_action(OrderAction.BUY, self.deep.bid_count)).format | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_get_market_snapshot(filled_order_book: Callable[[], OrderBook]) -> NoReturn:\n book = filled_order_book\n\n snapshot = book.get_market_snapshot()\n\n assert len(snapshot['asks']) == book.depth\n assert len(snapshot['bids']) == book.depth\n\n asks_prices = [ask['price'] for ask in snapshot['... | [
"0.6772954",
"0.6265355",
"0.60531557",
"0.6049403",
"0.5982641",
"0.59300596",
"0.58924204",
"0.5888865",
"0.5825112",
"0.5790062",
"0.57323784",
"0.5681437",
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"0.5588275",
"0.5558285",
"0.5555326",
"0.55443895",
"0.5522842",
"0.55121446",
"0.55108... | 0.53932893 | 27 |
Converts the auto incremented id of a ShortURL object and turns it into a shorturl hash | def encode(shorturl_id: int) -> str:
short_resource = []
while shorturl_id > 0:
character_index = shorturl_id % BASE
short_resource.append(CHARACTER_SPACE[character_index])
shorturl_id //= BASE
return "".join(short_resource[::-1]) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def shortURLToId(self, shortURL):\n id = 0\n for i in shortURL: \n val_i = ord(i) \n if(val_i >= ord('a') and val_i <= ord('z')): \n id = id*62 + val_i - ord('a') \n elif(val_i >= ord('A') and val_i <= ord('Z')): \n id = id*62 + val_i - o... | [
"0.7222362",
"0.6813473",
"0.6670428",
"0.6613821",
"0.6553491",
"0.6440487",
"0.6438503",
"0.6381131",
"0.6311566",
"0.62947756",
"0.6259774",
"0.62407327",
"0.620263",
"0.61301494",
"0.61228126",
"0.6112265",
"0.6034276",
"0.59468937",
"0.5900785",
"0.5891555",
"0.58526796"... | 0.69266266 | 1 |
Overrides the save to initially save to get the id then computes the shorturl hash and saves it to the model within a transaction context | def save(self, **kwargs):
res = super().save(**kwargs)
short_path_component = encode(res.id)
self.validated_data["short_path_component"] = short_path_component
return super().save(**kwargs) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def save(self,\n force_insert=False,\n force_update=False,\n using=None,\n update_fields=None):\n # If the short url wasn't specified\n if not self.short_url:\n # We pass the model instance that is being saved\n self.short_url = cr... | [
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"0.6860182",
"0.6255863",
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"0.6149716",
"0.61207795",
"0.60940796",
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"0.6051648",
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"0.60015386",
"0.5995751",
"0.5987927",
"0.5978799",
"0.5970341",
"0.5942499",
"0.5940011... | 0.6772935 | 2 |
Each line has a width of 100 units. Each character's width may be many units wide. This function will return the number of lines required to write out a string, as well as how many units were used in the last line. | def numberOfLines(self, widths, S):
# create a storage for the number of lines and current line's width
lineCount = 1
lineWidth = 0
for c in S:
# find the width of c by getting the index and retrieving the
# width from the widths list
cWidth = widths[ord(c) - ord('a')]
# add width to current line... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def longlines(x):\n return sum(len(plain(line)) // cw for line in x.split(\"\\n\"))",
"def get_width(self):\n return max(map(len, self.get_lines()))",
"def _label_width(text):\n width = 0\n for lineno, line in enumerate(text.split(u'\\n')):\n size = [_BIG_FONT, _SMALL_FONT][lineno > ... | [
"0.64796424",
"0.64689755",
"0.6344055",
"0.63050586",
"0.6292749",
"0.62515736",
"0.6186615",
"0.6142328",
"0.6140158",
"0.61232287",
"0.6122727",
"0.61053264",
"0.6101904",
"0.6101904",
"0.60962397",
"0.60413265",
"0.6031096",
"0.60083973",
"0.59954613",
"0.59206414",
"0.59... | 0.61721885 | 7 |
Attempt to place mover into contents. Returns a Boolean representation of success. | def contain(self, mover):
# Check if mover can exit old location
old_location = mover.location
if(not old_location):
return False
if(not old_location.allow_exit(mover)):
return False
# Check if mover can enter current location
if(not self.allow_ent... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def move(self) -> bool:\n pass",
"def allow_entry(self, mover):\n return True",
"def test_object_move(self):\n self.assertTrue(self.obj1 in self.room1.contents)\n # use move_to hook\n self.obj1.move_to(self.room2)\n self.assertFalse(self.obj1 in self.room1.contents)\n ... | [
"0.5737424",
"0.5638439",
"0.5441351",
"0.5409434",
"0.5399845",
"0.5309671",
"0.52931213",
"0.5276102",
"0.5168468",
"0.5082271",
"0.50646865",
"0.505076",
"0.50131536",
"0.50104046",
"0.50004804",
"0.4979135",
"0.49734983",
"0.4963041",
"0.49610388",
"0.49543136",
"0.495197... | 0.7234833 | 0 |
Determines if the mover is permitted to enter the room | def allow_entry(self, mover):
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def allowedToEnter(self):\n if base.cr.isPaid():\n return True\n place = base.cr.playGame.getPlace()\n myHoodId = ZoneUtil.getCanonicalHoodId(place.zoneId)\n if myHoodId in \\\n (ToontownGlobals.ToontownCentral,\n ToontownGlobals.MyEstate,\n T... | [
"0.6933369",
"0.6317256",
"0.6274393",
"0.6119734",
"0.6043591",
"0.6006229",
"0.59973824",
"0.5966571",
"0.59650975",
"0.59650975",
"0.5949079",
"0.590017",
"0.58607984",
"0.5843126",
"0.5832102",
"0.58177775",
"0.57856125",
"0.57780486",
"0.5743955",
"0.57223856",
"0.572238... | 0.66670233 | 1 |
Determines if the mover is permitted to exit the room. | def allow_exit(self, mover):
return True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def has_exited(self):\n agents = self.board[self.agent_locs_idx]\n return agents & (CellTypes.agent | CellTypes.exit) == CellTypes.exit",
"def can_exit(self) -> bool:\n return False",
"def check_exit(self, position, direction):\n if self.get_room((position[0] + direction[0], positio... | [
"0.6301413",
"0.6263654",
"0.62400985",
"0.60136616",
"0.58825636",
"0.58812755",
"0.58409286",
"0.5794512",
"0.5793184",
"0.5782265",
"0.5782265",
"0.57529366",
"0.5692975",
"0.5673591",
"0.56546485",
"0.56517553",
"0.5650926",
"0.5650613",
"0.5642109",
"0.56175417",
"0.5615... | 0.7196453 | 0 |
Called after the mover has entered the room. | def entered(self, mover):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def exited(self, mover):\n pass",
"def after_turn(self):\n pass",
"def game_over(self):\n self.end_of_level()\n self.message_holder.add_widget(self.you_lose_label)\n Clock.schedule_once(self.goto_menu, 5)",
"def end_of_level(self):\n Clock.unschedule(self.update)\n ... | [
"0.6746905",
"0.6695229",
"0.66767555",
"0.63322276",
"0.627838",
"0.627838",
"0.6254879",
"0.6229721",
"0.6191655",
"0.61626804",
"0.60663325",
"0.6041078",
"0.598377",
"0.59339255",
"0.5903108",
"0.585522",
"0.5828244",
"0.5815816",
"0.5759303",
"0.57528126",
"0.5750263",
... | 0.75459206 | 0 |
Called after the mover has exited the room. | def exited(self, mover):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def leave(self):\n self.pleaseQuit=1",
"def on_pre_leave(self):\n Logger.info('Application: Leaving the Intro screen.')",
"def on_pre_leave(self):\n Logger.info('Application: Leaving the Intro screen.')",
"def endGame(self):\n pass",
"def on_client_exit(self, game) -> None:\n ... | [
"0.6788173",
"0.65788233",
"0.65788233",
"0.65397877",
"0.6511395",
"0.6485533",
"0.6424921",
"0.6411908",
"0.64101607",
"0.6407878",
"0.637953",
"0.63781476",
"0.6357803",
"0.6351377",
"0.63508695",
"0.6343258",
"0.6334145",
"0.63243484",
"0.62887913",
"0.6288441",
"0.627727... | 0.78373396 | 0 |
Creates a tree from list. First element is root value, others are children nodes. (values or subtrees). | def construct(lst):
t = Tree()
t.root = lst[0]
for node in lst[1:]:
if isinstance(node, list):
t.nodes.append(construct(node))
else:
t.nodes.append(node)
return t | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_tree(tree_list, nums):\n\n if len(nums) == 0:\n return tree_list\n next_list = []\n j = 0\n for i in tree_list:\n for _ in range(2):\n if i is not None and j < len(nums):\n if nums[j] is No... | [
"0.70470774",
"0.69341266",
"0.6903691",
"0.6826804",
"0.67401844",
"0.6710746",
"0.65991884",
"0.6522682",
"0.63863814",
"0.6339975",
"0.63145685",
"0.63064444",
"0.6274908",
"0.6264302",
"0.62484676",
"0.62479275",
"0.6221631",
"0.62191725",
"0.6189883",
"0.6159182",
"0.615... | 0.7338503 | 0 |
A small test method for ticking. | def tick(self):
self.count += 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tick(self, tick):\n pass",
"def tick(self, tick):\n pass",
"def tick(self):",
"def tick(self):\n pass",
"def tick(self):\n pass",
"def tick(self):\r\n pass",
"def tick(self):\n return True",
"def tick(self, dt):\n pass",
"def _tick(self):\n\t\tse... | [
"0.7585349",
"0.7585349",
"0.7569551",
"0.7563374",
"0.7563374",
"0.7549485",
"0.7092856",
"0.7018002",
"0.6987178",
"0.69818205",
"0.6821981",
"0.6712875",
"0.66921383",
"0.66777706",
"0.6638356",
"0.66231155",
"0.6546713",
"0.65091604",
"0.6470777",
"0.64506656",
"0.6409298... | 0.61954355 | 34 |
A method to make all the objects necessary for testing. | def setUp(self):
self.simulation = FooSimulation(count=5, g=6, h=9, i=12)
self.foo = Foo(simulation=self.simulation, name='foo', a=4, b=42, c="Hello")
self.handler = Handler(ProxyLock(self.simulation),
ProxyLock(self.foo),
[Attribute(... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_objects(self):\n pass",
"def test_constructor(self):\n pass",
"def setUpClass(cls):\r\n cls.jon = Person.create(name='Jon', age=143)\r\n cls.eric = Person.create(name='Eric', age=25)\r\n cls.blake = Person.create(name='Blake', age=14)\r\n\r\n cls.physics = Cou... | [
"0.7469929",
"0.71140385",
"0.7040179",
"0.6990236",
"0.68704045",
"0.68704045",
"0.68704045",
"0.68704045",
"0.68704045",
"0.68704045",
"0.6843066",
"0.68285465",
"0.68145835",
"0.6789554",
"0.67843175",
"0.67811996",
"0.67123467",
"0.6711415",
"0.6684922",
"0.66496056",
"0.... | 0.0 | -1 |
A test to see if the packets get processed correctly. | def test_process_packet(self):
packet = {'a': 7}
self.assertEqual(self.foo.a, 4)
self.handler.process_packet(packet)
self.assertEqual(self.foo.a, 7)
packet = {'b': 9, 'a': 20}
self.handler.process_packet(packet)
self.assertEqual(self.foo.a, 20)
self.assert... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pes_packet_check_formedness(payload):\n b1 = ord(payload[0])\n b2 = ord(payload[1])\n b3 = ord(payload[2])\n\n b4 = ord(payload[3])\n if b1 != 0 or b2 != 0 or b3 != 1:\n return False\n return True",
"def test_process_packet_message(self):\n\n pkt = {'type': 'message',\n ... | [
"0.6842402",
"0.67776984",
"0.6636898",
"0.6476315",
"0.638278",
"0.6337137",
"0.6315716",
"0.6269154",
"0.6244437",
"0.61474615",
"0.6122378",
"0.60583025",
"0.60583025",
"0.6045686",
"0.6007994",
"0.6007994",
"0.6007165",
"0.59843373",
"0.59433156",
"0.59417355",
"0.5931659... | 0.6646249 | 2 |
A test to make sure that the handler collects the right information. | def test_prepare_packet(self):
self.handler.prepare_packet()
self.foo.c = "World"
self.foo.b = 21
self.simulation.tick()
packet = self.handler.prepare_packet()
self.assertEqual(packet['b'], 21)
self.assertEqual(packet['count'], 6)
for key in ['g', 'c', 'a'... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_init_adds_handler(self):\n pass",
"def test_handle(self):\n with pytest.raises(NotImplementedError):\n self.handler.handle(MagicMock())",
"def test_handle_basic(self):\n response = self.handler.handle(self.request, '/')\n\n self.view.assert_called_with(self.reque... | [
"0.71886176",
"0.71320015",
"0.7119762",
"0.71087456",
"0.700912",
"0.69731605",
"0.6775578",
"0.6775131",
"0.6685757",
"0.6584737",
"0.6575072",
"0.65643466",
"0.654191",
"0.6502415",
"0.64595646",
"0.64021575",
"0.63768643",
"0.63718456",
"0.63311636",
"0.63125056",
"0.6312... | 0.0 | -1 |
convert list of dicts to ndarray of type np.float32 | def dicts2ndarray(data_dicts):
# NEVER make any assumption about the order of .keys() return
aps = [ap for ap in data_dicts[0].keys() if ap != 'tag']
aps.sort()
data_num = len(data_dicts)
data_len = len(data_dicts[0][aps[0]])
ndary = np.zeros([data_num, len(aps), data_len], dtype=np.float32)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def translate_pandas_to_numpy(data_list:list) -> list:\n list_size = len(data_list)\n for i in range(list_size):\n data_list[i] = data_list[i].values.astype('float32')\n return data_list",
"def convert_dict_to_ndarray(*dictionaries):\n\n array_list = []\n\n # Loop all dicts\n for dictio... | [
"0.6651815",
"0.65400195",
"0.61362433",
"0.6098978",
"0.60989004",
"0.60879093",
"0.60031056",
"0.59976625",
"0.59976625",
"0.59976625",
"0.59841895",
"0.59794885",
"0.5843597",
"0.5822316",
"0.5761593",
"0.57518655",
"0.57207453",
"0.57119364",
"0.571017",
"0.570412",
"0.56... | 0.70575464 | 0 |
process raw data according to method given | def process(self, method):
process_dicts = []
for d in self.data_dicts:
dd = copy.deepcopy(d)
for ap in self.aps:
dd[ap] = method(d[ap])
process_dicts.append(dict2str(dd))
# print(process_dicts)
# print(type(process_dicts[0]))
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def process_data(self, data):\n return data",
"def processor(self, data):\n streaming_data = self.decoder.decodeData(data)\n # Add Your code here to process data and handle transport/storage",
"def processor(self, data):\n streaming_data = self.decoder.decodeData(data)\n # Ad... | [
"0.72334456",
"0.6959639",
"0.6959639",
"0.6959639",
"0.6959639",
"0.6959639",
"0.6959639",
"0.6871298",
"0.6871298",
"0.68358284",
"0.6817933",
"0.6815306",
"0.67331237",
"0.6659602",
"0.66281915",
"0.65316874",
"0.6517139",
"0.6490532",
"0.6486199",
"0.64807916",
"0.6477415... | 0.5911429 | 54 |
Assembles a list of circuits into a qobj which can be run on the backend. | def assemble_circuits(circuits, run_config=None, qobj_header=None, qobj_id=None):
qobj_header = qobj_header or QobjHeader()
run_config = run_config or RunConfig()
if isinstance(circuits, QuantumCircuit):
circuits = [circuits]
userconfig = QobjConfig(**run_config.to_dict())
experiments = []
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def assemble_circuits(circuits, qobj_id=None, qobj_header=None, run_config=None):\n qobj_config = QasmQobjConfig()\n if run_config:\n qobj_config = QasmQobjConfig(**run_config.to_dict())\n\n # Pack everything into the Qobj\n experiments = []\n max_n_qubits = 0\n max_memory_slots = 0\n f... | [
"0.7279348",
"0.6496389",
"0.59102285",
"0.5772845",
"0.57442355",
"0.5727163",
"0.55746835",
"0.55432576",
"0.55362433",
"0.5509834",
"0.5474253",
"0.5412955",
"0.5407767",
"0.53782344",
"0.53507787",
"0.53283745",
"0.5326846",
"0.5310684",
"0.52896637",
"0.52684003",
"0.526... | 0.69339204 | 1 |
Convert all config sections to have unique names. Adds unique suffixes to config sections for compability with configparser. | def unique_config_sections(config_file):
section_counters = defaultdict(int)
output_stream = io.StringIO()
with open(config_file) as fin:
for line in fin:
if line.startswith('['):
section = line.strip().strip('[]')
_section = section + '_' + str(section_co... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fix_compname_configs(ibs):\n # ibs.MANUAL_CONFIG_SUFFIX = '_MANUAL_' #+ ut.get_computer_name()\n # ibs.MANUAL_CONFIGID = ibs.add_config(ibs.MANUAL_CONFIG_SUFFIX)\n # We need to fix the manual config suffix to not use computer names anymore\n\n configid_list = ibs.get_valid_configids()\n cfgsuff... | [
"0.6045993",
"0.5563847",
"0.5368636",
"0.5358432",
"0.5267798",
"0.51614577",
"0.51502544",
"0.5139199",
"0.5124081",
"0.50915194",
"0.507346",
"0.50681233",
"0.49954256",
"0.4976946",
"0.49577245",
"0.49545503",
"0.4944312",
"0.492063",
"0.4905497",
"0.490392",
"0.48970628"... | 0.5965138 | 1 |
The last value for the W array is correct | def test_W_end(self):
self.assertAlmostEqual(attempt.W[-1], 9.494852380803035) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def w(self) -> np.ndarray:\n return self.array[:, 0] if self.scalar_vector else self.array[:, 3]",
"def get_w(self, i_order):\n\n return np.array([]), np.array([])",
"def w(self) -> float:\n return self.A[0] if self.scalar_vector else self.A[3]",
"def new_w(w, d):\n\n if w.sum() > 0:\... | [
"0.6439141",
"0.6317358",
"0.6140997",
"0.60708946",
"0.60476446",
"0.6045793",
"0.6034233",
"0.5948805",
"0.5945211",
"0.58441013",
"0.58261454",
"0.5818163",
"0.57634544",
"0.5760683",
"0.5717286",
"0.5704453",
"0.5694879",
"0.5665707",
"0.5622648",
"0.56216794",
"0.5620351... | 0.639363 | 1 |
The last value for the Z array is correct | def test_Z_end(self):
self.assertAlmostEqual(attempt.Z[-1], 41.47999849170943) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def z(self):\n return self._arr[2]",
"def z(self):\n return self._data[2]",
"def get_lz(self):\r\n return self.dz * self.nz - self.oz",
"def relu(Z):\n\n A = np.maximum(0, Z)\n\n assert (A.shape == Z.shape)\n\n return A",
"def z(self):\r\n return self.unif[2]",
"def z(sel... | [
"0.72840196",
"0.66340685",
"0.6575737",
"0.6572709",
"0.65650034",
"0.65324533",
"0.65268767",
"0.65268767",
"0.65268767",
"0.6514927",
"0.64908797",
"0.64388865",
"0.6430518",
"0.64048165",
"0.6372679",
"0.6338418",
"0.6318305",
"0.62974244",
"0.6289918",
"0.6280703",
"0.62... | 0.6586646 | 2 |
The first value for the W array is correct | def test_W_start(self):
self.assertAlmostEqual(attempt.W[0], 12) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def w(self) -> np.ndarray:\n return self.array[:, 0] if self.scalar_vector else self.array[:, 3]",
"def w(self) -> float:\n return self.A[0] if self.scalar_vector else self.A[3]",
"def get_w(self, i_order):\n\n return np.array([]), np.array([])",
"def __init__(self, w):\n self.w =... | [
"0.6571864",
"0.63333076",
"0.62975305",
"0.6284889",
"0.60969466",
"0.60714823",
"0.599055",
"0.5986858",
"0.59700614",
"0.5932216",
"0.585418",
"0.58040833",
"0.5794119",
"0.5789142",
"0.5787203",
"0.5778182",
"0.57695913",
"0.57609683",
"0.573644",
"0.5735926",
"0.57335657... | 0.59087545 | 10 |
The first value for the Z array is correct | def test_Z_start(self):
self.assertAlmostEqual(attempt.Z[0], 40) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def z(self):\n return self._arr[2]",
"def z(self) -> float:\n return self.A[3] if self.scalar_vector else self.A[2]",
"def z(self):\n return self._data[2]",
"def z(self):\r\n return self.unif[2]",
"def z(self):\n return self[:, 2]",
"def z(self):\n return self.coords... | [
"0.73199224",
"0.6729115",
"0.6569211",
"0.6560481",
"0.6554395",
"0.6549071",
"0.6405089",
"0.63656455",
"0.63523674",
"0.6309033",
"0.6308248",
"0.63073283",
"0.6301584",
"0.6276863",
"0.6261062",
"0.6253484",
"0.6253484",
"0.6253484",
"0.62091494",
"0.618319",
"0.61823267"... | 0.64692014 | 6 |
The arrays all have the correct lengths | def test_lengths(self):
self.assertEqual(size(attempt.Z), 201)
self.assertEqual(size(attempt.W), 201) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def array(self):",
"def test_ncols_vrt_array(self):\n self.assertEqual(_test_array(landsat_vrt).shape[2], 235)",
"def test_has_correct_length(self) -> None:\n assert len(list(self._dataset)) == 7168",
"def test_nbands_vrt_array(self):\n self.assertEqual(_test_array(landsat_vrt).shape[0],... | [
"0.6665907",
"0.6437724",
"0.6414497",
"0.6371735",
"0.62632823",
"0.61963075",
"0.6181136",
"0.6181136",
"0.6171587",
"0.6137263",
"0.61063594",
"0.6080566",
"0.6074043",
"0.6025451",
"0.6017989",
"0.5976124",
"0.59638834",
"0.594764",
"0.5943476",
"0.59414154",
"0.5932839",... | 0.0 | -1 |
The maxIndex variables are correct | def test_maxIndex(self):
self.assertEqual(attempt.maxIndexZ, 113)
self.assertEqual(attempt.maxIndexW, 134) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def maxQualifiedIndex(self, indices):\n entry = self.getConfig()\n # the leader keep its own record updated to the newest\n indices[self.datacenter_id] = len(self.log) - 1\n # print('!!!!!', indices)\n if entry['config'] == 'single':\n return sorted([indices[x] for x i... | [
"0.7089196",
"0.67561334",
"0.67561334",
"0.67561334",
"0.6644873",
"0.6621024",
"0.65653",
"0.6489624",
"0.64309424",
"0.6412204",
"0.6361595",
"0.63488233",
"0.63382834",
"0.63159776",
"0.62829936",
"0.6254711",
"0.6254558",
"0.6239701",
"0.6237676",
"0.61731935",
"0.616580... | 0.7708999 | 0 |
Parses ansible facts file in JSON format to discover drives. Required facts in the format are shown below. { ... | def get_devices():
try:
with open(DEVICES, 'r') as f:
data = json.load(f)['devices']
except (IOError, ValueError) as err:
raise SwiftlmCheckFailure('Failure opening %s: %s' % (DEVICES, err))
devices = []
for d in data:
l = d.get('label', LABEL_CHECK_DISABLED)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_hostsdata_from_hostsfile(hosts_file) -> dict:\n\n if not os.path.isfile(hosts_file):\n logger.error(f\"Suzieq inventory {hosts_file} must be a file\")\n print(f\"ERROR: Suzieq inventory {hosts_file} must be a file\")\n sys.exit(1)\n\n if not os.access(hosts_file, os.R_OK):\n ... | [
"0.62157637",
"0.59848344",
"0.59457314",
"0.5934885",
"0.5726563",
"0.56022584",
"0.5492696",
"0.548934",
"0.544715",
"0.5425406",
"0.53883463",
"0.5386127",
"0.5320267",
"0.530013",
"0.5203763",
"0.5157003",
"0.5150875",
"0.51109576",
"0.499665",
"0.49880725",
"0.49814734",... | 0.48628756 | 31 |
Checks mount point is owned by swift | def is_ug_swift(d, r):
stats = os.stat(d.mount)
uid = stats.st_uid
gid = stats.st_gid
user = pwd.getpwuid(uid).pw_name
group = grp.getgrgid(gid).gr_name
if user == group == 'swift':
return True
else:
r.msgkey('user', user)
r.msgkey('group', group)
return Fals... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ownercheck(self, userhost):\n if self.cfg and self.cfg.owner:\n if userhost in self.cfg.owner: return True\n return False",
"def _check_mounted_system(self):\n res = self.su_cmd('touch /system/.dwarf_check')\n if res == '':\n res = self._do_adb_command('shell... | [
"0.6451464",
"0.6307461",
"0.6153694",
"0.6151752",
"0.61308235",
"0.6095205",
"0.60757345",
"0.60000616",
"0.5997545",
"0.5997545",
"0.5976451",
"0.59735596",
"0.5972847",
"0.5931066",
"0.59120023",
"0.59047663",
"0.58646756",
"0.58345026",
"0.5809635",
"0.5780444",
"0.57620... | 0.6578928 | 0 |
Checks the relevant swift mount points and diskusage | def main():
results = []
results.extend(check_mounts())
results.extend(diskusage())
return results | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _check_mounted_system(self):\n res = self.su_cmd('touch /system/.dwarf_check')\n if res == '':\n res = self._do_adb_command('shell ls -la /system')\n if '.dwarf_check' in res:\n res = self.su_cmd('rm /system/.dwarf_check')\n if res == '':\n ... | [
"0.65840626",
"0.6307514",
"0.6279391",
"0.626951",
"0.6082033",
"0.60685736",
"0.60032076",
"0.5917685",
"0.5890955",
"0.58835125",
"0.5840331",
"0.58330125",
"0.5823619",
"0.58203804",
"0.5819363",
"0.581247",
"0.58020556",
"0.5750178",
"0.5736998",
"0.5730349",
"0.5725064"... | 0.6437659 | 1 |
Return a transformed Variable if there is a large (>12) shift. | def get_offset(self):
if self.shift >= 12 and not isinstance(self, OffsetVariable):
return OffsetVariable(
rank=self.rank,
name=self.name,
shift=self.shift,
units=self.units,
parent=self.parent,
)
ret... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def read12bit(self, register):\n valuearray = bytearray(self.device.readregistermulti(register, 2))\n return struct.unpack('!H', valuearray)[0] & ((2 ** 12) - 1) # Convert to short and discard first four bits",
"def len12(self): # -> Any | float:\n ...",
"def shift(self):\n return ... | [
"0.54482156",
"0.5174691",
"0.48559287",
"0.48548213",
"0.4682742",
"0.46447504",
"0.46120813",
"0.46117097",
"0.45603758",
"0.45588163",
"0.45473444",
"0.44411454",
"0.44405517",
"0.44322982",
"0.44162038",
"0.44104075",
"0.43977198",
"0.43933216",
"0.43922186",
"0.43858984",
... | 0.5158371 | 2 |
The inverse of `get_offset()`. | def get_standard(self):
if self.shift >= 12 and isinstance(self, OffsetVariable):
return StandardVariable(
rank=self.rank,
name=self.name,
shift=self.shift,
units=self.units,
parent=self.parent,
)
ret... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Offset(self) -> int:",
"def Offset(self) -> int:",
"def Offset(self) -> int:",
"def offset(self, offset):\n raise NotImplementedError(\"This should have been implemented.\")",
"def get_offset(self):\n return self.offset",
"def offset(self):\n return self.__offset",
"def offset(... | [
"0.84163034",
"0.84163034",
"0.84163034",
"0.78482765",
"0.7759836",
"0.77160716",
"0.77160716",
"0.76086974",
"0.75559103",
"0.75314885",
"0.75314885",
"0.75314885",
"0.75314885",
"0.75314885",
"0.75314885",
"0.75314885",
"0.75008124",
"0.74963164",
"0.74358535",
"0.72741544",... | 0.0 | -1 |
Add the fill params if needed. | def _fill_root(self):
if self.parent in filled_variables:
return f"{self.name} {st_persistent_perc}P {st_k}k"
return self.name | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fill_missing_parameters(self):\n pseudo_id = self.get_param_by_type(PseudoID)\n pseudo_name = self.get_param_by_type(PseudoName)\n if pseudo_id is None and pseudo_name is not None:\n self.parameters.append(\n PseudoID(pseudo_name.value)\n ) # take name... | [
"0.6528969",
"0.63597214",
"0.6197034",
"0.61547756",
"0.6130784",
"0.61055094",
"0.6097497",
"0.5999343",
"0.59145826",
"0.5904964",
"0.5889323",
"0.5852561",
"0.58364487",
"0.58171743",
"0.57736933",
"0.5735036",
"0.5718243",
"0.56878495",
"0.56824",
"0.56730765",
"0.567059... | 0.0 | -1 |
Add the fill params if needed. | def _nn_fill_root(self):
if self.parent in filled_variables:
return f"{self.name} {nn_n_months}NN"
return self.name | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fill_missing_parameters(self):\n pseudo_id = self.get_param_by_type(PseudoID)\n pseudo_name = self.get_param_by_type(PseudoName)\n if pseudo_id is None and pseudo_name is not None:\n self.parameters.append(\n PseudoID(pseudo_name.value)\n ) # take name... | [
"0.6528969",
"0.63597214",
"0.6197034",
"0.61547756",
"0.6130784",
"0.61055094",
"0.6097497",
"0.5999343",
"0.59145826",
"0.5904964",
"0.5889323",
"0.5852561",
"0.58364487",
"0.58171743",
"0.57736933",
"0.5735036",
"0.5718243",
"0.56878495",
"0.56824",
"0.56730765",
"0.567059... | 0.0 | -1 |
Filled name (if applicable). | def filled(self):
if self.parent in filled_variables:
return f"{self._fill_root} {self.shift}M"
return self._fill_root | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def name(self, name):\n pass",
"def name():\n pass",
"def name():\n pass",
"def getName(self):\n return \"\"",
"def name_field(self):\r\n return 'name'",
"def test_name_empty_string(self):\r\n self.name = \"\"",
"def name(self) -> str: # pragma: no cover",... | [
"0.69951504",
"0.6751056",
"0.6751056",
"0.67024434",
"0.6659543",
"0.6640836",
"0.65940964",
"0.65553534",
"0.65237314",
"0.6510735",
"0.64991957",
"0.64991957",
"0.64991957",
"0.64991957",
"0.64991957",
"0.647957",
"0.647957",
"0.647957",
"0.647957",
"0.6468007",
"0.6453826... | 0.0 | -1 |
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