How to use _setup method in Molotov

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Setup.py

Source:Setup.py Github

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1import warnings2import numpy as np3import json4import os5import datetime6import glob7import re8import ntpath9import shutil10from keras.models import load_model11class Setup(object):12 def __init__(self, name):13 self._name = name14 self._model = None15 self._emptyModel = None16 self._training_ids = None17 self._validation_ids = None18 self._testing_ids = None19 self._training_data = None20 self._validation_data = None21 self._testing_data = None22 self._training_targets = None23 self._validation_targets = None24 self._testing_targets = None25 self._training_ids_directory = None26 self._validation_ids_directory = None27 self._testing_ids_directory = None28 self._training_data_directory = None29 self._validation_data_directory = None30 self._testing_data_directory = None31 self._training_targets_directory = None32 self._validation_targets_directory = None33 self._testing_targets_directory = None34 self._training_accuracy = []35 self._training_auc = []36 self._training_loss = []37 self._validation_accuracy = []38 self._validation_auc = []39 self._validation_loss = []40 self._testing_accuracy = []41 self._testing_auc = []42 self._testing_loss = []43 self._batch_size = None44 self._epochs = 045 self._others = {}46 self._setup = {47 'name': self._name,48 'file': {49 'setup': '',50 'model': '',51 'model_arch_json': '',52 'model_arch_yaml': '',53 'model_weights': '',54 'training_ids': '',55 'validation_ids': '',56 'testing_ids': '',57 'training_data': '',58 'validation_data': '',59 'testing_data': '',60 'training_targets': '',61 'validation_targets': '',62 'testing_targets': '',63 },64 'directory': {65 'training_ids': '',66 'validation_ids': '',67 'testing_ids': '',68 'training_data': '',69 'validation_data': '',70 'testing_data': '',71 'training_targets': '',72 'validation_targets': '',73 'testing_targets': '',74 },75 'training_accuracy': self._training_accuracy,76 'training_accuracy': self._training_auc,77 'training_loss': self._training_loss,78 'validation_accuracy': self._validation_accuracy,79 'validation_accuracy': self._validation_auc,80 'validation_loss': self._validation_loss,81 'testing_accuracy': self._testing_accuracy,82 'testing_accuracy': self._testing_auc,83 'testing_loss': self._testing_loss,84 'epochs': self._epochs,85 'others': self._others,86 }87 def getName(self):88 return self._name89 def setName(self, name):90 self._name = name91 def getModel(self):92 return self._model93 def setModel(self, model):94 self._model = model95 # TODO: get the empty model and assign it to self._emptyModel96 def getData(self):97 return self._training_ids, self._training_data, self._training_targets, \98 self._validation_ids, self._validation_data, self._validation_targets, \99 self._testing_ids, self._testing_data, self._testing_targets100 def setData(self,101 training_ids=None, training_data=None, training_targets=None,102 validation_ids=None, validation_data=None, validation_targets=None,103 testing_ids=None, testing_data=None, testing_targets=None):104 self._training_ids = training_ids if training_ids is not None else self._training_ids105 self._validation_ids = validation_ids if validation_ids is not None else self._validation_ids106 self._testing_ids = testing_ids if testing_ids is not None else self._testing_ids107 self._training_data = training_data if training_data is not None else self._training_data108 self._validation_data = validation_data if validation_data is not None else self._validation_data109 self._testing_data = testing_data if testing_data is not None else self._testing_data110 self._training_targets = training_targets if training_targets is not None else self._training_targets111 self._validation_targets = validation_targets if validation_targets is not None else self._validation_targets112 self._testing_targets = testing_targets if testing_targets is not None else self._testing_targets113 def getDataDirectory(self):114 return self._training_data_directory, self._training_data_directory, self._training_targets_directory, \115 self._validation_data_directory, self._validation_data_directory, self._validation_targets_directory, \116 self._testing_data_directory, self._testing_data_directory, self._testing_targets_directory117 def setDataDirectory(self,118 training_ids_directory=None, training_data_directory=None, training_targets_directory=None,119 validation_ids_directory=None, validation_data_directory=None, validation_targets_directory=None,120 testing_ids_directory=None, testing_data_directory=None, testing_targets_directory=None):121 self._training_ids_directory = training_ids_directory if training_ids_directory is not None else self._training_ids_directory122 self._validation_ids_directory = validation_ids_directory if validation_ids_directory is not None else self._validation_ids_directory123 self._testing_ids_directory = testing_ids_directory if testing_ids_directory is not None else self._testing_ids_directory124 self._training_data_directory = training_data_directory if training_data_directory is not None else self._training_data_directory125 self._validation_data_directory = validation_data_directory if validation_data_directory is not None else self._validation_data_directory126 self._testing_data_directory = testing_data_directory if testing_data_directory is not None else self._testing_data_directory127 self._training_targets_directory = training_targets_directory if training_targets_directory is not None else self._training_targets_directory128 self._validation_targets_directory = validation_targets_directory if validation_targets_directory is not None else self._validation_targets_directory129 self._testing_targets_directory = testing_targets_directory if testing_targets_directory is not None else self._testing_targets_directory130 def getEpoch(self):131 return self._epochs132 def updateEpochs(self, add_epochs,133 training_acc, training_auc, training_loss,134 validation_acc, validation_auc, validation_loss,135 testing_acc, testing_auc, testing_loss,136 allow_modify=True):137 # TODO: check138 def checkListLength(length, mList, listName, allowModify):139 modifiedList = mList140 if allow_modify:141 if len(modifiedList) < length:142 modifiedList.extend([mList[-1] for i in range(length - len(modifiedList))])143 elif len(modifiedList) > length:144 warnings.warn('%s list is longer than add_epochs. Trimmed list will be used.' % listName)145 modifiedList = modifiedList[:length]146 else:147 if len(modifiedList) != length:148 raise ValueError('%s list length is not equal to add_epochs' % listName)149 return modifiedList150 # Checking parameters151 # add_epochs152 if add_epochs is None or type(add_epochs) != int:153 raise TypeError('add_epochs should have type \'int\'')154 elif add_epochs < 0:155 raise ValueError('add_epochs should be > 0')156 if training_acc is None or type(training_acc) != list or \157 training_auc is None or type(training_auc) != list or \158 training_loss is None or type(training_loss) != list or \159 validation_acc is None or type(validation_acc) != list or \160 validation_auc is None or type(validation_auc) != list or \161 validation_loss is None or type(validation_loss) != list or \162 testing_acc is None or type(testing_acc) != list or \163 testing_auc is None or type(testing_auc) != list or \164 testing_loss is None or type(testing_loss) != list:165 raise TypeError('training_acc, training_auc, training_loss, '166 'validation_acc, validation_auc, validation_loss, '167 'testing_acc, testing_auc, testing_loss should have type \'list\'')168 new_train_acc = checkListLength(add_epochs, training_acc, 'training_acc', allow_modify)169 new_train_auc = checkListLength(add_epochs, training_auc, 'training_auc', allow_modify)170 new_train_loss = checkListLength(add_epochs, training_loss, 'training_loss', allow_modify)171 new_val_acc = checkListLength(add_epochs, validation_acc, 'validation_acc', allow_modify)172 new_val_auc = checkListLength(add_epochs, validation_auc, 'validation_auc', allow_modify)173 new_val_loss = checkListLength(add_epochs, validation_loss, 'validation_loss', allow_modify)174 new_test_acc = checkListLength(add_epochs, testing_acc, 'testing_acc', allow_modify)175 new_test_auc = checkListLength(add_epochs, testing_auc, 'testing_auc', allow_modify)176 new_test_loss = checkListLength(add_epochs, testing_loss, 'testing_loss', allow_modify)177 self._epochs += add_epochs178 self._training_accuracy.extend(new_train_acc)179 self._training_auc.extend(new_train_auc)180 self._training_loss.extend(new_train_loss)181 self._validation_accuracy.extend(new_val_acc)182 self._validation_auc.extend(new_val_auc)183 self._validation_loss.extend(new_val_loss)184 self._testing_accuracy.extend(new_test_acc)185 self._testing_auc.extend(new_test_auc)186 self._testing_loss.extend(new_test_loss)187 def getOthers(self):188 return self._others189 def setOthers(self, others):190 for key in others:191 self._others[key] = others[key]192 def save(self, rel_path):193 # Save every information or object194 if rel_path is None:195 raise ValueError('rel_path should not be None')196 else:197 pass198 self._setup['name'] = self._name199 self._setup['time'] = str(datetime.datetime.now()),200 self._setup['file']['setup'] = os.path.join('setup.json')201 self._setup['file']['model'] = os.path.join('model.h5')202 self._setup['file']['model_arch_json'] = os.path.join('model_architecture.json')203 self._setup['file']['model_arch_yaml'] = os.path.join('model_architecture.yaml')204 self._setup['file']['model_weights'] = os.path.join('model_weights.h5')205 self._setup['file']['training_ids'] = os.path.join('training_ids.npy')206 self._setup['file']['validation_ids'] = os.path.join('validation_ids.npy')207 self._setup['file']['testing_ids'] = os.path.join('testing_ids.npy')208 self._setup['file']['training_data'] = os.path.join('training_data.npy')209 self._setup['file']['validation_data'] = os.path.join('validation_data.npy')210 self._setup['file']['testing_data'] = os.path.join('testing_data.npy')211 self._setup['file']['training_targets'] = os.path.join('training_targets.npy')212 self._setup['file']['validation_targets'] = os.path.join('validation_targets.npy')213 self._setup['file']['testing_targets'] = os.path.join('testing_targets.npy')214 self._setup['directory']['training_ids'] = self._training_ids_directory215 self._setup['directory']['validation_ids'] = self._validation_ids_directory216 self._setup['directory']['testing_ids'] = self._testing_ids_directory217 self._setup['directory']['training_data'] = self._training_data_directory218 self._setup['directory']['validation_data'] = self._validation_data_directory219 self._setup['directory']['testing_data'] = self._testing_data_directory220 self._setup['directory']['training_targets'] = self._training_targets_directory221 self._setup['directory']['validation_targets'] = self._validation_targets_directory222 self._setup['directory']['testing_targets'] = self._testing_targets_directory223 self._setup['training_accuracy'] = self._training_accuracy224 self._setup['training_auc'] = self._training_auc225 self._setup['training_loss'] = self._training_loss226 self._setup['validation_accuracy'] = self._validation_accuracy227 self._setup['validation_auc'] = self._validation_auc228 self._setup['validation_loss'] = self._validation_loss229 self._setup['testing_accuracy'] = self._testing_accuracy230 self._setup['testing_auc'] = self._testing_auc231 self._setup['testing_loss'] = self._testing_loss232 self._setup['epochs'] = self._epochs233 self._setup['others'] = self._others234 if not os.path.exists(os.path.join(os.getcwd(), rel_path)):235 os.mkdir(os.path.join(os.getcwd(), rel_path))236 if not os.path.exists(os.path.join(os.getcwd(), rel_path, self._name)):237 os.mkdir(os.path.join(os.getcwd(), rel_path, self._name))238 if len(glob.glob(os.path.join(os.getcwd(), rel_path, self._name, '*.*'))) > 0:239 versions = []240 pattern = r'^.*version(?P<versionnumber>\d*)$'241 for dir in glob.glob(os.path.join(os.getcwd(), rel_path, self._name, 'version*')):242 regex = re.search(pattern, dir)243 versions.append(int(regex.group('versionnumber')))244 if len(versions) == 0:245 maxVer = 0246 else:247 maxVer = np.max(versions)248 newVerDirName = 'version%s' % (maxVer + 1)249 os.mkdir(os.path.join(os.getcwd(), rel_path, self._name, newVerDirName))250 self._backup_version(os.path.join(os.getcwd(), rel_path, self._name),251 os.path.join(os.getcwd(), rel_path, self._name, newVerDirName))252 if (maxVer + 1 - 10) > 0 and (maxVer + 1 - 10) % 20 != 0:253 oldVerDirName = 'version%s' % (maxVer + 1 - 10)254 shutil.rmtree(os.path.join(os.getcwd(), rel_path, self._name, oldVerDirName))255 # ==========================================256 # Save whole model257 self._model.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['model']))258 # ==========================================259 # Save model architecture260 json_model_arch = self._model.to_json()261 with open(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['model_arch_json']), 'w') as jsonfile:262 jsonfile.write(json_model_arch)263 yaml_model_arch = self._model.to_yaml()264 with open(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['model_arch_yaml']), 'w') as yamlfile:265 yamlfile.write(yaml_model_arch)266 # ==========================================267 # Save model weights268 self._model.save_weights(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['model_weights']))269 # ==========================================270 # Save data271 if self._training_ids is not None and type(self._training_ids) == np.ndarray:272 try:273 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['training_ids']), self._training_ids)274 except Exception as e:275 self._setup['file']['training_ids'] = None276 if self._validation_ids is not None and type(self._validation_ids) == np.ndarray:277 try:278 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['validation_ids']), self._validation_ids)279 except Exception as e:280 self._setup['file']['validation_ids'] = None281 if self._testing_ids is not None and type(self._testing_ids) == np.ndarray:282 try:283 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['testing_ids']), self._testing_ids)284 except Exception as e:285 self._setup['file']['testing_ids'] = None286 if self._training_data is not None and type(self._training_data) == np.ndarray:287 try:288 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['training_data']), self._training_data)289 except Exception as e:290 self._setup['file']['training_data'] = None291 if self._validation_data is not None and type(self._validation_data) == np.ndarray:292 try:293 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['validation_data']), self._validation_data)294 except Exception as e:295 self._setup['file']['validation_data'] = None296 if self._testing_data is not None and type(self._testing_data) == np.ndarray:297 try:298 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['testing_data']), self._testing_data)299 except Exception as e:300 self._setup['file']['testing_data'] = None301 if self._training_targets is not None and type(self._training_targets) == np.ndarray:302 try:303 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['training_targets']), self._training_targets)304 except Exception as e:305 self._setup['file']['training_targets'] = None306 if self._validation_targets is not None and type(self._validation_targets) == np.ndarray:307 try:308 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['validation_targets']), self._validation_targets)309 except Exception as e:310 self._setup['file']['validation_targets'] = None311 if self._testing_targets is not None and type(self._testing_targets) == np.ndarray:312 try:313 np.save(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['testing_targets']), self._testing_targets)314 except Exception as e:315 self._setup['file']['testing_targets'] = None316 # ==========================================317 # Save setup318 with open(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['setup']), 'w') as setupfile:319 json.dump(self._setup, setupfile)320 def load(self, rel_filepath):321 cwd = os.getcwd()322 if rel_filepath is None:323 raise ValueError('rel_filepath should be None')324 else:325 pass326 # ==========================================327 # Load info328 with open(os.path.join(cwd, rel_filepath), 'r') as setupfile:329 self._setup = json.load(setupfile)330 rel_filepath = rel_filepath.replace('setup.json', '')331 # ==========================================332 # Load name333 self._name = self._setup['name']334 # ==========================================335 # Load whole model336 self._model = load_model(os.path.join(cwd, rel_filepath, self._setup['file']['model']))337 # TODO: if loading from model h5 file fails, then load from model arch file and load weights338 # # ==========================================339 # # Load model architecture340 # with open(os.path.join(directory, self.setup['model_arch_json']), 'r') as jsonfile:341 # self.emptyModel = model_from_json(jsonfile.read())342 #343 # with open(os.path.join(directory, self.setup['model_arch_yaml']), 'r') as yamlfile:344 # self.emptyModel = model_from_yaml(yamlfile.read())345 # # ==========================================346 # # Load model weights347 # self.model.load_weights(os.path.join(directory, self.setup['model_weights']))348 # ==========================================349 # Load data350 self._training_ids = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['training_ids'])) \351 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['training_ids'])) else self._training_ids352 self._validation_ids = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['validation_ids'])) \353 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['validation_ids'])) else self._validation_ids354 self._testing_ids = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['testing_ids'])) \355 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['testing_ids'])) else self._testing_ids356 self._training_data = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['training_data'])) \357 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['training_data'])) else self._training_data358 self._validation_data = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['validation_data'])) \359 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['validation_data'])) else self._validation_data360 self._testing_data = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['testing_data'])) \361 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['testing_data'])) else self._testing_data362 self._training_targets = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['training_targets'])) \363 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['training_targets'])) else self._training_targets364 self._validation_targets = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['validation_targets'])) \365 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['validation_targets'])) else self._validation_targets366 self._testing_targets = np.load(os.path.join(cwd, rel_filepath, self._setup['file']['testing_targets'])) \367 if os.path.exists(os.path.join(cwd, rel_filepath, self._setup['file']['testing_targets'])) else self._testing_targets368 # ==========================================369 # Load data directory370 self._training_data_directory = self._setup['directory']['training_data']371 self._validation_data_directory = self._setup['directory']['validation_data']372 self._testing_data_directory = self._setup['directory']['testing_data']373 self._training_targets_directory = self._setup['directory']['training_targets']374 self._validation_targets_directory = self._setup['directory']['validation_targets']375 self._testing_targets_directory = self._setup['directory']['testing_targets']376 # ==========================================377 # Load info378 self._training_accuracy = self._setup['training_accuracy']379 self._training_auc = self._setup['training_auc']380 self._training_loss = self._setup['training_loss']381 self._validation_accuracy = self._setup['validation_accuracy']382 self._validation_auc = self._setup['validation_auc']383 self._validation_loss = self._setup['validation_loss']384 self._testing_accuracy = self._setup['testing_accuracy']385 self._testing_auc = self._setup['testing_auc']386 self._testing_loss = self._setup['testing_loss']387 self._epochs = self._setup['epochs']388 self._others = self._setup['others']389 def save_setupfile(self, rel_path):390 with open(os.path.join(os.getcwd(), rel_path, self._name, self._setup['file']['setup']), 'w') as setupfile:391 json.dump(self._setup, setupfile)392 def _backup_version(self, source, destination):393 ignore_list = ['training_data',394 'validation_data',395 'testing_data',396 'training_targets',397 'validation_targets',398 'testing_targets']399 for file in glob.glob(os.path.join(source, '*.*')):400 ignore = False401 for ignored_filename in ignore_list:402 if ignored_filename in file:403 ignore = True404 if ignore:405 continue406 else:...

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test_scales.py

Source:test_scales.py Github

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...25 @pytest.fixture26 def x(self):27 return pd.Series([1, 3, 9], name="x", dtype=float)28 def setup_ticks(self, x, *args, **kwargs):29 s = Continuous().tick(*args, **kwargs)._setup(x, Coordinate())30 a = PseudoAxis(s._matplotlib_scale)31 a.set_view_interval(0, 1)32 return a33 def setup_labels(self, x, *args, **kwargs):34 s = Continuous().label(*args, **kwargs)._setup(x, Coordinate())35 a = PseudoAxis(s._matplotlib_scale)36 a.set_view_interval(0, 1)37 locs = a.major.locator()38 return a, locs39 def test_coordinate_defaults(self, x):40 s = Continuous()._setup(x, Coordinate())41 assert_series_equal(s(x), x)42 def test_coordinate_transform(self, x):43 s = Continuous(trans="log")._setup(x, Coordinate())44 assert_series_equal(s(x), np.log10(x))45 def test_coordinate_transform_with_parameter(self, x):46 s = Continuous(trans="pow3")._setup(x, Coordinate())47 assert_series_equal(s(x), np.power(x, 3))48 def test_coordinate_transform_error(self, x):49 s = Continuous(trans="bad")50 with pytest.raises(ValueError, match="Unknown value provided"):51 s._setup(x, Coordinate())52 def test_interval_defaults(self, x):53 s = Continuous()._setup(x, IntervalProperty())54 assert_array_equal(s(x), [0, .25, 1])55 def test_interval_with_range(self, x):56 s = Continuous((1, 3))._setup(x, IntervalProperty())57 assert_array_equal(s(x), [1, 1.5, 3])58 def test_interval_with_norm(self, x):59 s = Continuous(norm=(3, 7))._setup(x, IntervalProperty())60 assert_array_equal(s(x), [-.5, 0, 1.5])61 def test_interval_with_range_norm_and_transform(self, x):62 x = pd.Series([1, 10, 100])63 # TODO param order?64 s = Continuous((2, 3), (10, 100), "log")._setup(x, IntervalProperty())65 assert_array_equal(s(x), [1, 2, 3])66 def test_color_defaults(self, x):67 cmap = color_palette("ch:", as_cmap=True)68 s = Continuous()._setup(x, Color())69 assert_array_equal(s(x), cmap([0, .25, 1])[:, :3]) # FIXME RGBA70 def test_color_named_values(self, x):71 cmap = color_palette("viridis", as_cmap=True)72 s = Continuous("viridis")._setup(x, Color())73 assert_array_equal(s(x), cmap([0, .25, 1])[:, :3]) # FIXME RGBA74 def test_color_tuple_values(self, x):75 cmap = color_palette("blend:b,g", as_cmap=True)76 s = Continuous(("b", "g"))._setup(x, Color())77 assert_array_equal(s(x), cmap([0, .25, 1])[:, :3]) # FIXME RGBA78 def test_color_callable_values(self, x):79 cmap = color_palette("light:r", as_cmap=True)80 s = Continuous(cmap)._setup(x, Color())81 assert_array_equal(s(x), cmap([0, .25, 1])[:, :3]) # FIXME RGBA82 def test_color_with_norm(self, x):83 cmap = color_palette("ch:", as_cmap=True)84 s = Continuous(norm=(3, 7))._setup(x, Color())85 assert_array_equal(s(x), cmap([-.5, 0, 1.5])[:, :3]) # FIXME RGBA86 def test_color_with_transform(self, x):87 x = pd.Series([1, 10, 100], name="x", dtype=float)88 cmap = color_palette("ch:", as_cmap=True)89 s = Continuous(trans="log")._setup(x, Color())90 assert_array_equal(s(x), cmap([0, .5, 1])[:, :3]) # FIXME RGBA91 def test_tick_locator(self, x):92 locs = [.2, .5, .8]93 locator = mpl.ticker.FixedLocator(locs)94 a = self.setup_ticks(x, locator)95 assert_array_equal(a.major.locator(), locs)96 def test_tick_locator_input_check(self, x):97 err = "Tick locator must be an instance of .*?, not <class 'tuple'>."98 with pytest.raises(TypeError, match=err):99 Continuous().tick((1, 2))100 def test_tick_upto(self, x):101 for n in [2, 5, 10]:102 a = self.setup_ticks(x, upto=n)103 assert len(a.major.locator()) <= (n + 1)104 def test_tick_every(self, x):105 for d in [.05, .2, .5]:106 a = self.setup_ticks(x, every=d)107 assert np.allclose(np.diff(a.major.locator()), d)108 def test_tick_every_between(self, x):109 lo, hi = .2, .8110 for d in [.05, .2, .5]:111 a = self.setup_ticks(x, every=d, between=(lo, hi))112 expected = np.arange(lo, hi + d, d)113 assert_array_equal(a.major.locator(), expected)114 def test_tick_at(self, x):115 locs = [.2, .5, .9]116 a = self.setup_ticks(x, at=locs)117 assert_array_equal(a.major.locator(), locs)118 def test_tick_count(self, x):119 n = 8120 a = self.setup_ticks(x, count=n)121 assert_array_equal(a.major.locator(), np.linspace(0, 1, n))122 def test_tick_count_between(self, x):123 n = 5124 lo, hi = .2, .7125 a = self.setup_ticks(x, count=n, between=(lo, hi))126 assert_array_equal(a.major.locator(), np.linspace(lo, hi, n))127 def test_tick_minor(self, x):128 n = 3129 a = self.setup_ticks(x, count=2, minor=n)130 # I am not sure why matplotlib's minor ticks include the131 # largest major location but exclude the smalllest one ...132 expected = np.linspace(0, 1, n + 2)[1:]133 assert_array_equal(a.minor.locator(), expected)134 def test_log_tick_default(self, x):135 s = Continuous(trans="log")._setup(x, Coordinate())136 a = PseudoAxis(s._matplotlib_scale)137 a.set_view_interval(.5, 1050)138 ticks = a.major.locator()139 assert np.allclose(np.diff(np.log10(ticks)), 1)140 def test_log_tick_upto(self, x):141 n = 3142 s = Continuous(trans="log").tick(upto=n)._setup(x, Coordinate())143 a = PseudoAxis(s._matplotlib_scale)144 assert a.major.locator.numticks == n145 def test_log_tick_count(self, x):146 with pytest.raises(RuntimeError, match="`count` requires"):147 Continuous(trans="log").tick(count=4)148 s = Continuous(trans="log").tick(count=4, between=(1, 1000))149 a = PseudoAxis(s._setup(x, Coordinate())._matplotlib_scale)150 a.set_view_interval(.5, 1050)151 assert_array_equal(a.major.locator(), [1, 10, 100, 1000])152 def test_log_tick_every(self, x):153 with pytest.raises(RuntimeError, match="`every` not supported"):154 Continuous(trans="log").tick(every=2)155 def test_symlog_tick_default(self, x):156 s = Continuous(trans="symlog")._setup(x, Coordinate())157 a = PseudoAxis(s._matplotlib_scale)158 a.set_view_interval(-1050, 1050)159 ticks = a.major.locator()160 assert ticks[0] == -ticks[-1]161 pos_ticks = np.sort(np.unique(np.abs(ticks)))162 assert np.allclose(np.diff(np.log10(pos_ticks[1:])), 1)163 assert pos_ticks[0] == 0164 def test_label_formatter(self, x):165 fmt = mpl.ticker.FormatStrFormatter("%.3f")166 a, locs = self.setup_labels(x, fmt)167 labels = a.major.formatter.format_ticks(locs)168 for text in labels:169 assert re.match(r"^\d\.\d{3}$", text)170 def test_label_like_pattern(self, x):171 a, locs = self.setup_labels(x, like=".4f")172 labels = a.major.formatter.format_ticks(locs)173 for text in labels:174 assert re.match(r"^\d\.\d{4}$", text)175 def test_label_like_string(self, x):176 a, locs = self.setup_labels(x, like="x = {x:.1f}")177 labels = a.major.formatter.format_ticks(locs)178 for text in labels:179 assert re.match(r"^x = \d\.\d$", text)180 def test_label_like_function(self, x):181 a, locs = self.setup_labels(x, like="{:^5.1f}".format)182 labels = a.major.formatter.format_ticks(locs)183 for text in labels:184 assert re.match(r"^ \d\.\d $", text)185 def test_label_base(self, x):186 a, locs = self.setup_labels(100 * x, base=2)187 labels = a.major.formatter.format_ticks(locs)188 for text in labels[1:]:189 assert not text or "2^" in text190 def test_label_unit(self, x):191 a, locs = self.setup_labels(1000 * x, unit="g")192 labels = a.major.formatter.format_ticks(locs)193 for text in labels[1:-1]:194 assert re.match(r"^\d+ mg$", text)195 def test_label_unit_with_sep(self, x):196 a, locs = self.setup_labels(1000 * x, unit=("", "g"))197 labels = a.major.formatter.format_ticks(locs)198 for text in labels[1:-1]:199 assert re.match(r"^\d+mg$", text)200 def test_label_empty_unit(self, x):201 a, locs = self.setup_labels(1000 * x, unit="")202 labels = a.major.formatter.format_ticks(locs)203 for text in labels[1:-1]:204 assert re.match(r"^\d+m$", text)205 def test_label_base_from_transform(self, x):206 s = Continuous(trans="log")207 a = PseudoAxis(s._setup(x, Coordinate())._matplotlib_scale)208 a.set_view_interval(10, 1000)209 label, = a.major.formatter.format_ticks([100])210 assert r"10^{2}" in label211 def test_label_type_checks(self):212 s = Continuous()213 with pytest.raises(TypeError, match="Label formatter must be"):214 s.label("{x}")215 with pytest.raises(TypeError, match="`like` must be"):216 s.label(like=2)217class TestNominal:218 @pytest.fixture219 def x(self):220 return pd.Series(["a", "c", "b", "c"], name="x")221 @pytest.fixture222 def y(self):223 return pd.Series([1, -1.5, 3, -1.5], name="y")224 def test_coordinate_defaults(self, x):225 s = Nominal()._setup(x, Coordinate())226 assert_array_equal(s(x), np.array([0, 1, 2, 1], float))227 def test_coordinate_with_order(self, x):228 s = Nominal(order=["a", "b", "c"])._setup(x, Coordinate())229 assert_array_equal(s(x), np.array([0, 2, 1, 2], float))230 def test_coordinate_with_subset_order(self, x):231 s = Nominal(order=["c", "a"])._setup(x, Coordinate())232 assert_array_equal(s(x), np.array([1, 0, np.nan, 0], float))233 def test_coordinate_axis(self, x):234 ax = mpl.figure.Figure().subplots()235 s = Nominal()._setup(x, Coordinate(), ax.xaxis)236 assert_array_equal(s(x), np.array([0, 1, 2, 1], float))237 f = ax.xaxis.get_major_formatter()238 assert f.format_ticks([0, 1, 2]) == ["a", "c", "b"]239 def test_coordinate_axis_with_order(self, x):240 order = ["a", "b", "c"]241 ax = mpl.figure.Figure().subplots()242 s = Nominal(order=order)._setup(x, Coordinate(), ax.xaxis)243 assert_array_equal(s(x), np.array([0, 2, 1, 2], float))244 f = ax.xaxis.get_major_formatter()245 assert f.format_ticks([0, 1, 2]) == order246 def test_coordinate_axis_with_subset_order(self, x):247 order = ["c", "a"]248 ax = mpl.figure.Figure().subplots()249 s = Nominal(order=order)._setup(x, Coordinate(), ax.xaxis)250 assert_array_equal(s(x), np.array([1, 0, np.nan, 0], float))251 f = ax.xaxis.get_major_formatter()252 assert f.format_ticks([0, 1, 2]) == [*order, ""]253 def test_coordinate_axis_with_category_dtype(self, x):254 order = ["b", "a", "d", "c"]255 x = x.astype(pd.CategoricalDtype(order))256 ax = mpl.figure.Figure().subplots()257 s = Nominal()._setup(x, Coordinate(), ax.xaxis)258 assert_array_equal(s(x), np.array([1, 3, 0, 3], float))259 f = ax.xaxis.get_major_formatter()260 assert f.format_ticks([0, 1, 2, 3]) == order261 def test_coordinate_numeric_data(self, y):262 ax = mpl.figure.Figure().subplots()263 s = Nominal()._setup(y, Coordinate(), ax.yaxis)264 assert_array_equal(s(y), np.array([1, 0, 2, 0], float))265 f = ax.yaxis.get_major_formatter()266 assert f.format_ticks([0, 1, 2]) == ["-1.5", "1.0", "3.0"]267 def test_coordinate_numeric_data_with_order(self, y):268 order = [1, 4, -1.5]269 ax = mpl.figure.Figure().subplots()270 s = Nominal(order=order)._setup(y, Coordinate(), ax.yaxis)271 assert_array_equal(s(y), np.array([0, 2, np.nan, 2], float))272 f = ax.yaxis.get_major_formatter()273 assert f.format_ticks([0, 1, 2]) == ["1.0", "4.0", "-1.5"]274 def test_color_defaults(self, x):275 s = Nominal()._setup(x, Color())276 cs = color_palette()277 assert_array_equal(s(x), [cs[0], cs[1], cs[2], cs[1]])278 def test_color_named_palette(self, x):279 pal = "flare"280 s = Nominal(pal)._setup(x, Color())281 cs = color_palette(pal, 3)282 assert_array_equal(s(x), [cs[0], cs[1], cs[2], cs[1]])283 def test_color_list_palette(self, x):284 cs = color_palette("crest", 3)285 s = Nominal(cs)._setup(x, Color())286 assert_array_equal(s(x), [cs[0], cs[1], cs[2], cs[1]])287 def test_color_dict_palette(self, x):288 cs = color_palette("crest", 3)289 pal = dict(zip("bac", cs))290 s = Nominal(pal)._setup(x, Color())291 assert_array_equal(s(x), [cs[1], cs[2], cs[0], cs[2]])292 def test_color_numeric_data(self, y):293 s = Nominal()._setup(y, Color())294 cs = color_palette()295 assert_array_equal(s(y), [cs[1], cs[0], cs[2], cs[0]])296 def test_color_numeric_with_order_subset(self, y):297 s = Nominal(order=[-1.5, 1])._setup(y, Color())298 c1, c2 = color_palette(n_colors=2)299 null = (np.nan, np.nan, np.nan)300 assert_array_equal(s(y), [c2, c1, null, c1])301 @pytest.mark.xfail(reason="Need to sort out float/int order")302 def test_color_numeric_int_float_mix(self):303 z = pd.Series([1, 2], name="z")304 s = Nominal(order=[1.0, 2])._setup(z, Color())305 c1, c2 = color_palette(n_colors=2)306 null = (np.nan, np.nan, np.nan)307 assert_array_equal(s(z), [c1, null, c2])308 def test_color_alpha_in_palette(self, x):309 cs = [(.2, .2, .3, .5), (.1, .2, .3, 1), (.5, .6, .2, 0)]310 s = Nominal(cs)._setup(x, Color())311 assert_array_equal(s(x), [cs[0], cs[1], cs[2], cs[1]])312 def test_color_unknown_palette(self, x):313 pal = "not_a_palette"314 err = f"{pal} is not a valid palette name"315 with pytest.raises(ValueError, match=err):316 Nominal(pal)._setup(x, Color())317 def test_object_defaults(self, x):318 class MockProperty(ObjectProperty):319 def _default_values(self, n):320 return list("xyz"[:n])321 s = Nominal()._setup(x, MockProperty())322 assert s(x) == ["x", "y", "z", "y"]323 def test_object_list(self, x):324 vs = ["x", "y", "z"]325 s = Nominal(vs)._setup(x, ObjectProperty())326 assert s(x) == ["x", "y", "z", "y"]327 def test_object_dict(self, x):328 vs = {"a": "x", "b": "y", "c": "z"}329 s = Nominal(vs)._setup(x, ObjectProperty())330 assert s(x) == ["x", "z", "y", "z"]331 def test_object_order(self, x):332 vs = ["x", "y", "z"]333 s = Nominal(vs, order=["c", "a", "b"])._setup(x, ObjectProperty())334 assert s(x) == ["y", "x", "z", "x"]335 def test_object_order_subset(self, x):336 vs = ["x", "y"]337 s = Nominal(vs, order=["a", "c"])._setup(x, ObjectProperty())338 assert s(x) == ["x", "y", None, "y"]339 def test_objects_that_are_weird(self, x):340 vs = [("x", 1), (None, None, 0), {}]341 s = Nominal(vs)._setup(x, ObjectProperty())342 assert s(x) == [vs[0], vs[1], vs[2], vs[1]]343 def test_alpha_default(self, x):344 s = Nominal()._setup(x, Alpha())345 assert_array_equal(s(x), [.95, .625, .3, .625])346 def test_fill(self):347 x = pd.Series(["a", "a", "b", "a"], name="x")348 s = Nominal()._setup(x, Fill())349 assert_array_equal(s(x), [True, True, False, True])350 def test_fill_dict(self):351 x = pd.Series(["a", "a", "b", "a"], name="x")352 vs = {"a": False, "b": True}353 s = Nominal(vs)._setup(x, Fill())354 assert_array_equal(s(x), [False, False, True, False])355 def test_fill_nunique_warning(self):356 x = pd.Series(["a", "b", "c", "a", "b"], name="x")357 with pytest.warns(UserWarning, match="The variable assigned to fill"):358 s = Nominal()._setup(x, Fill())359 assert_array_equal(s(x), [True, False, True, True, False])360 def test_interval_defaults(self, x):361 class MockProperty(IntervalProperty):362 _default_range = (1, 2)363 s = Nominal()._setup(x, MockProperty())364 assert_array_equal(s(x), [2, 1.5, 1, 1.5])365 def test_interval_tuple(self, x):366 s = Nominal((1, 2))._setup(x, IntervalProperty())367 assert_array_equal(s(x), [2, 1.5, 1, 1.5])368 def test_interval_tuple_numeric(self, y):369 s = Nominal((1, 2))._setup(y, IntervalProperty())370 assert_array_equal(s(y), [1.5, 2, 1, 2])371 def test_interval_list(self, x):372 vs = [2, 5, 4]373 s = Nominal(vs)._setup(x, IntervalProperty())374 assert_array_equal(s(x), [2, 5, 4, 5])375 def test_interval_dict(self, x):376 vs = {"a": 3, "b": 4, "c": 6}377 s = Nominal(vs)._setup(x, IntervalProperty())378 assert_array_equal(s(x), [3, 6, 4, 6])379 def test_interval_with_transform(self, x):380 class MockProperty(IntervalProperty):381 _forward = np.square382 _inverse = np.sqrt383 s = Nominal((2, 4))._setup(x, MockProperty())384 assert_array_equal(s(x), [4, np.sqrt(10), 2, np.sqrt(10)])385class TestTemporal:386 @pytest.fixture387 def t(self):388 dates = pd.to_datetime(["1972-09-27", "1975-06-24", "1980-12-14"])389 return pd.Series(dates, name="x")390 @pytest.fixture391 def x(self, t):392 return pd.Series(mpl.dates.date2num(t), name=t.name)393 def test_coordinate_defaults(self, t, x):394 s = Temporal()._setup(t, Coordinate())395 assert_array_equal(s(t), x)396 def test_interval_defaults(self, t, x):397 s = Temporal()._setup(t, IntervalProperty())398 normed = (x - x.min()) / (x.max() - x.min())399 assert_array_equal(s(t), normed)400 def test_interval_with_range(self, t, x):401 values = (1, 3)402 s = Temporal((1, 3))._setup(t, IntervalProperty())403 normed = (x - x.min()) / (x.max() - x.min())404 expected = normed * (values[1] - values[0]) + values[0]405 assert_array_equal(s(t), expected)406 def test_interval_with_norm(self, t, x):407 norm = t[1], t[2]408 s = Temporal(norm=norm)._setup(t, IntervalProperty())409 n = mpl.dates.date2num(norm)410 normed = (x - n[0]) / (n[1] - n[0])411 assert_array_equal(s(t), normed)412 def test_color_defaults(self, t, x):413 cmap = color_palette("ch:", as_cmap=True)414 s = Temporal()._setup(t, Color())415 normed = (x - x.min()) / (x.max() - x.min())416 assert_array_equal(s(t), cmap(normed)[:, :3]) # FIXME RGBA417 def test_color_named_values(self, t, x):418 name = "viridis"419 cmap = color_palette(name, as_cmap=True)420 s = Temporal(name)._setup(t, Color())421 normed = (x - x.min()) / (x.max() - x.min())422 assert_array_equal(s(t), cmap(normed)[:, :3]) # FIXME RGBA423 def test_coordinate_axis(self, t, x):424 ax = mpl.figure.Figure().subplots()425 s = Temporal()._setup(t, Coordinate(), ax.xaxis)426 assert_array_equal(s(t), x)427 locator = ax.xaxis.get_major_locator()428 formatter = ax.xaxis.get_major_formatter()429 assert isinstance(locator, mpl.dates.AutoDateLocator)430 assert isinstance(formatter, mpl.dates.AutoDateFormatter)431 @pytest.mark.skipif(432 Version(mpl.__version__) < Version("3.3.0"),433 reason="Test requires new matplotlib date epoch."434 )435 def test_tick_locator(self, t):436 locator = mpl.dates.YearLocator(month=3, day=15)437 s = Temporal().tick(locator)438 a = PseudoAxis(s._setup(t, Coordinate())._matplotlib_scale)439 a.set_view_interval(0, 365)440 assert 73 in a.major.locator()441 def test_tick_upto(self, t, x):442 n = 8443 ax = mpl.figure.Figure().subplots()444 Temporal().tick(upto=n)._setup(t, Coordinate(), ax.xaxis)445 locator = ax.xaxis.get_major_locator()446 assert set(locator.maxticks.values()) == {n}447 @pytest.mark.skipif(448 Version(mpl.__version__) < Version("3.3.0"),449 reason="Test requires new matplotlib date epoch."450 )451 def test_label_formatter(self, t):452 formatter = mpl.dates.DateFormatter("%Y")453 s = Temporal().label(formatter)454 a = PseudoAxis(s._setup(t, Coordinate())._matplotlib_scale)455 a.set_view_interval(10, 1000)456 label, = a.major.formatter.format_ticks([100])457 assert label == "1970"458 def test_label_concise(self, t, x):459 ax = mpl.figure.Figure().subplots()460 Temporal().label(concise=True)._setup(t, Coordinate(), ax.xaxis)461 formatter = ax.xaxis.get_major_formatter()...

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trace_setup.py

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1from enum import Enum2from pathlib import Path3from subprocess import CalledProcessError, check_output4import yaml5import re6import cxxfilt7class BinaryAlreadyAddedError(Exception):8 def __init__(self, message=''):9 super().__init__(message)10class BinaryNotExistsError(Exception):11 def __init__(self, message=''):12 super().__init__(message)13class ConfigFileError(Exception):14 def __init__(self, message=''):15 super().__init__(message)16class FunctionNotInBinaryError(Exception):17 def __init__(self, message=''):18 super().__init__(message)19class BuiltInNotExistsError(Exception):20 def __init__(self, message=''):21 super().__init__(message)22class Setup:23 def __init__(self):24 self._setup = {}25 # initialize app and its functions for tracing26 def initialize_binary(self, path):27 if path in self._setup:28 raise BinaryAlreadyAddedError('Binary at {} already added'.format(path))29 try:30 symbols = check_output(['nm', path]).decode().rstrip().split('\n')31 except CalledProcessError:32 raise BinaryNotExistsError33 functions = [symbol.split()[-1] for symbol in symbols]34 init_state = {}35 for function in functions:36 try:37 name = cxxfilt.demangle(function)38 except cxxfilt.InvalidName:39 name = function40 init_state[name] = {41 'mangled': function,42 'traced': False,43 'parameters': {},44 'offset': 045 }46 self._setup[path] = init_state47 # search offset after setting stack pointer for built-in function48 def get_offset_for_built_in(self, func_name):49 offset = 050 try:51 # search address of function in symbol map52 sym_address = check_output(53 ['sudo',54 'grep',55 '-A1',56 '-w',57 func_name,58 '/proc/kallsyms']59 ).decode().rstrip().split('\n')60 if len(sym_address) == 2:61 # address of given function62 start_address = -163 start_address_match = re.search(r'^([a-f0-9]+)', sym_address[0])64 if start_address_match:65 start_address = int(start_address_match.group(1), base=16)66 # address of following symbol67 stop_address = -168 stop_address_match = re.search(r'^([a-f0-9]+)', sym_address[1])69 if stop_address_match:70 stop_address = int(stop_address_match.group(1), base=16)71 if start_address >= 0 and stop_address >= 0:72 # get instructions of function73 objdump_out = check_output(74 ['sudo',75 'objdump',76 '--prefix-addresses',77 '-d',78 '--start-address=0x{:X}'.format(start_address),79 '--stop-address=0x{:X}'.format(stop_address),80 '/proc/kcore']81 ).decode().rstrip().split('\n')82 # search first instruction after function prologue83 first = False84 second = False85 for line in objdump_out:86 if first and second:87 func_offset = re.search(r'(0x[a-f0-9]+)', line)88 if func_offset:89 # needed offset is difference between function's base address and90 # address of first instruction after function prologue91 offset = int(func_offset.group(1), base=16) - start_address92 break93 # second instruction of function prologue94 if first and re.search(r'mov\s+%rsp,%rbp', line):95 second = True96 # first instruction of function prologue97 if not(first) and re.search(r'push\s+%rbp', line):98 first = True99 except CalledProcessError:100 raise BuiltInNotExistsError101 return offset102 # initialize built-in function to be traced103 def initialize_built_in(self, func_name):104 if 'built-ins' not in self._setup:105 self._setup['built-ins'] = {}106 try:107 offset = self.get_offset_for_built_in(func_name)108 self._setup['built-ins'][func_name] = {109 'traced': True,110 'parameters': {},111 'offset': offset112 }113 except BuiltInNotExistsError:114 raise115 # Remove application from getting traced116 def remove_app(self, app):117 del self._setup[app]118 # Returns apps currently saved119 def get_apps(self):120 return list(self._setup.keys())121 # Return functions and their state of a given application122 def get_setup_of_app(self, app):123 return self._setup[app]124 # search offset after setting stack pointer for user function125 def get_offset_for_function(self, app_name, func_name):126 offset = 0127 # get instructions of function128 try:129 objdump_out = check_output(['objdump', "--disassemble="+func_name, "--prefix-addresses", app_name]).decode().rstrip().split('\n')130 except CalledProcessError:131 raise FunctionNotInBinaryError132 first = False133 second = False134 for line in objdump_out:135 if first and second:136 # first instruction after function prologue with offset137 func_offset = re.search(r'<'+func_name+r'\+(0x[a-f0-9]+)>', line)138 if func_offset:139 offset = int(func_offset.group(1), base=16)140 break141 # second instruction of function prologue142 if first and re.search(r'mov\s+%rsp,%rbp', line):143 second = True144 # first instruction of function prologue145 if not(first) and re.search(r'push\s+%rbp', line):146 first = True147 return offset148 # Sets up a function to be traced149 def setup_function_to_trace(self, app, function):150 try:151 self._setup[app][function]['traced'] = True152 offset = self.get_offset_for_function(app, function)153 self._setup[app][function]['offset'] = offset154 except KeyError:155 for func_name in self._setup[app]:156 if self._setup[app][func_name]['mangled'] == function:157 self._setup[app][func_name]['traced'] = True158 offset = self.get_offset_for_function(app, function)159 self._setup[app][func_name]['offset'] = offset160 return161 raise FunctionNotInBinaryError(162 'No function named {} was found in {}'.format(function, app)163 )164 # Removes a function from traced ones165 def remove_function_from_trace(self, app, function):166 try:167 self._setup[app][function]['traced'] = False168 except KeyError:169 for func_name in self._setup[app]:170 if self._setup[app][func_name]['mangled'] == function:171 self._setup[app][func_name]['traced'] = False172 return173 raise FunctionNotInBinaryError(174 'No function named {} was found in {}'.format(function, app)175 )176 # Returns the indexes where a parameter is set for tracing177 def get_parameters(self, app, function):178 return self._setup[app][function]['parameters']179 # Sets up a parameter to be traced180 def add_parameter(self, app, function, index, format):181 self._setup[app][function]['parameters'][index] = format182 # Removes a parameter from traced ones183 def remove_parameter(self, app, function, index):184 del self._setup[app][function]['parameters'][index]185 # Convert dictionary of functions to trace into properly186 # structured list of args to be used by the trace tool187 def generate_bcc_args(self):188 arguments = []189 for app in self._setup:190 for function in self._setup[app]:191 if self._setup[app][function]['traced']:192 if app == 'built-ins':193 argument = '{}+0x{:X}'.format(function, self._setup[app][function]['offset'])194 else:195 argument = '{}:{}+0x{:X}'.format(app, self._setup[app][function]['mangled'], self._setup[app][function]['offset'])196 params = self._setup[app][function]['parameters']197 if params:198 argument = '{} "{}", {}'.format(199 argument,200 ' '.join([params[index] for index in params]),201 ', '.join(['arg{}'.format(index) for index in params]))202 arguments.append(argument)203 return arguments204 def load_from_file(self, path):205 try:206 content = Path(path).read_text()207 except FileNotFoundError:208 raise ConfigFileError('Could not find config file at {}'.format(path))209 except IsADirectoryError:210 raise ConfigFileError('{} is a directory, not a file'.format(path))211 try:212 config = yaml.safe_load(content)213 except (yaml.parser.ParserError, yaml.scanner.ScannerError):214 raise ConfigFileError('File needs to be yaml format')215 err_message = ''216 for app in config:217 try:218 self.initialize_binary(app)219 for function in config[app]:220 self.setup_function_to_trace(app, function)221 for index in config[app][function]:222 self.add_parameter(app, function, index, config[app][function][index])223 except BinaryNotExistsError:224 try:225 self.initialize_built_in(app)226 for index in config[app]:227 self.add_parameter('built-ins', app, index, config[app][index])228 err_message = 'Some binaries were not found so they were assumed to be built-in functions'229 except BuiltInNotExistsError:230 err_message = 'Some binaries were not found, and neither as built-in functions'231 except TypeError:232 raise ConfigFileError('File format is incorrect')...

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Demux16Way.py

Source:Demux16Way.py Github

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...36 self.gate5 = Demux.Demux()37 self.gate6 = Demux.Demux()38 self.gate7 = Demux.Demux()39 self.gate8 = Demux.Demux()40 def _setup(self):41 self.gate0.a = self.a42 self.gate0.select = self.select[0:3]43 self.b = self.gate0.outaf()44 self.c = self.gate0.outbf()45 self.d = self.gate0.outcf()46 self.e = self.gate0.outdf()47 self.f = self.gate0.outef()48 self.g = self.gate0.outff()49 self.h = self.gate0.outgf()50 self.i = self.gate0.outhf()51 self.gate1.a = self.b52 self.gate1.select = self.select[3:4]53 self.outa = self.gate1.outaf()54 self.outb = self.gate1.outbf()55 self.gate2.a = self.c56 self.gate2.select = self.select[3:4]57 self.outc = self.gate2.outaf()58 self.outd = self.gate2.outbf()59 self.gate3.a = self.d60 self.gate3.select = self.select[3:4]61 self.oute = self.gate3.outaf()62 self.outf = self.gate3.outbf()63 self.gate4.a = self.e64 self.gate4.select = self.select[3:4]65 self.outg = self.gate4.outaf()66 self.outh = self.gate4.outbf()67 self.gate5.a = self.f68 self.gate5.select = self.select[3:4]69 self.outi = self.gate5.outaf()70 self.outj = self.gate5.outbf()71 self.gate6.a = self.g72 self.gate6.select = self.select[3:4]73 self.outk = self.gate6.outaf()74 self.outl = self.gate6.outbf()75 self.gate7.a = self.h76 self.gate7.select = self.select[3:4]77 self.outm = self.gate7.outaf()78 self.outn = self.gate7.outbf()79 self.gate8.a = self.i80 self.gate8.select = self.select[3:4]81 self.outo = self.gate8.outaf()82 self.outp = self.gate8.outbf()83 def outaf(self):84 self._setup()85 return self.outa86 def outbf(self):87 self._setup()88 return self.outb89 def outcf(self):90 self._setup()91 return self.outc92 def outdf(self):93 self._setup()94 return self.outd95 def outef(self):96 self._setup()97 return self.oute98 def outff(self):99 self._setup()100 return self.outf101 def outgf(self):102 self._setup()103 return self.outg104 def outhf(self):105 self._setup()106 return self.outh107 def outif(self):108 self._setup()109 return self.outi110 def outjf(self):111 self._setup()112 return self.outj113 def outkf(self):114 self._setup()115 return self.outk116 def outlf(self):117 self._setup()118 return self.outl119 def outmf(self):120 self._setup()121 return self.outm122 def outnf(self):123 self._setup()124 return self.outn125 def outof(self):126 self._setup()127 return self.outo128 def outpf(self):129 self._setup()...

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