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How to use _setup method in autotest

Best Python code snippet using autotest_python

Setup.py

Source:Setup.py

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:...

test_scales.py

Source:test_scales.py

...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()...

trace_setup.py

Source:trace_setup.py

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')...

Demux16Way.py

Source:Demux16Way.py

...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()...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.