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How to use load_by_type method in lisa

Best Python code snippet using lisa_python

cli.py

Source:cli.py

...123def list(component_type):124    """List components that are available on your machine"""125    config_loader = initialise_component_loader()126    component_types = sorted({127         "displays": lambda: config_loader.load_by_type(ComponentType.DISPLAY),128         "datafeeds": lambda: config_loader.load_by_type(ComponentType.DATA_FEED),129         "filters": lambda: config_loader.load_by_type(ComponentType.FILTER),130         "notifications": lambda: config_loader.load_by_type(ComponentType.NOTIFICATION)131    }.items(), key=lambda t: t[0])132    def print_ids(creators):133        ids = {c.id_key_value[1] if hasattr(c, "id_key_value") else c.get_id() for c in creators}134        for i in sorted(ids):135            click.echo(" - %s" % i)136    for k, v in component_types:137        if component_type == k or component_type == "all":138            click.echo("Available %s:" % k)139            print_ids(v())140        if component_type == "all":141            click.echo("")142def read_dashboard_from_config(dashboard_config, configs):143    try:144        return dashboard_config.read_yaml(configs)...

configuration.py

Source:configuration.py

...78        self._component_configs_loader = component_configs_loader79        self._secret_store = secrets80        self._initialise_parsers()81    def _initialise_parsers(self):82        display_configs = self._component_configs_loader.load_by_type(ComponentType.DISPLAY)83        self._display_config_section_parser = ComponentConfigParser(display_configs,  self._secret_store)84        data_feed_configs = self._component_configs_loader.load_by_type(ComponentType.DATA_FEED)85        self._data_feed_config_section_parser = ComponentConfigParser(data_feed_configs, self._secret_store)86        filter_configs = self._component_configs_loader.load_by_type(ComponentType.FILTER)87        filter_parser = ComponentConfigParser(filter_configs,  self._secret_store)88        notification_configs = \89            self._component_configs_loader.load_by_type(ComponentType.NOTIFICATION)90        self._notification_config_section_parser = NotificationComponentsConfigParser(91            notification_configs,92            filter_parser,93            self._secret_store94        )95    def read_yaml(self, yaml_configs):96        dashboards = []97        for yaml_config in yaml_configs:98            try:99                config = yaml.safe_load(yaml_config)100            except yaml.YAMLError as err:101                raise ConfigYamlParsingError(err, yaml_config)102            dashboards.append(self._create_dashboard(config))103        return self._dashboard_merger.merge(dashboards)...

load_scan.py

Source:load_scan.py

...4import matplotlib.pyplot as plt5from mpl_toolkits.mplot3d.art3d import Poly3DCollection6import numpy as np7from skimage import measure8def load_by_type(path, file_type, contains=""):9    return [10        dicom.read_file(os.path.join(path, s))11        for s in os.listdir(path)12        if s.startswith(file_type) and (contains in s)13    ]14def load_planning(path):15    plans = load_by_type(path, "RS.", contains="GTV")16    return plans17def load_slices(path):18    slices = load_by_type(path, "CT.")19    slices.sort(key=lambda x: int(x.InstanceNumber))20    try:21        slice_thickness = np.abs(22            slices[0].ImagePositionPatient[2] - slices[1].ImagePositionPatient[2]23        )24    except:25        slice_thickness = np.abs(slices[0].SliceLocation - slices[1].SliceLocation)26    for s in slices:27        s.SliceThickness = slice_thickness28    return slices29def load_scan(path):30    return {31        "slices": load_slices(path),32        "planning": load_planning(path),...

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