def __init__(self, name, **kwargs):
self.name = name
self.params = kwargs
try:
self.function = self.functions[name](**kwargs)
except KeyError as e:
self.errorUnknown(e)
raise exceptions.ConfigurationError()
except TypeError as e:
raise exceptions.ConfigurationError(e)
def load_YAML(fileObject):
try:
config = yaml.safe_load(fileObject)
except yaml.composer.ComposerError as e:
log.error(f"YAML composer error {e}")
raise exceptions.ConfigurationError(e) from e
except yaml.scanner.ScannerError as e:
log.error(f"YAML scanner error {e}")
raise exceptions.ConfigurationError(e) from e
return dotmap.DotMap(config)
def get_space(self, definition):
try:
if isinstance(definition, dotmap.DotMap):
return self.get_space_range(**definition.toDict())
elif isinstance(definition, numbers.Number) or isinstance(
definition, datetime.datetime):
return [definition]
else:
raise exceptions.ConfigurationError(
f"Parameter space definition must be either a number or a dictionary with min, max and count defined"
)
except TypeError as e:
raise exceptions.ConfigurationError(e)
def __init__(self, name, **kwargs):
self.name = name
self.params = kwargs
try:
self.sample = self.functions.get(name)(**kwargs)
except TypeError:
self.error_unknown(name)
raise exceptions.ConfigurationError()
def __init__(self, parameters, streaks=True):
log.debug(f"Initializing the population")
self.generator = Generator.from_config(parameters)
self.parameters = parameters
self.streaks = streaks
try:
log.info("Configuring meteoroid property distributions")
except AttributeError as e:
raise exceptions.ConfigurationError(e) from e
def from_config(cls, config):
try:
return cls(config.distribution, **config.parameters.toDict())
except KeyError:
log.error("{cfg} is not a valid configuration option for {name}".format(
cfg = c.param(config),
name = c.name(cls.__name__)
))
log.error("Expected distribution name \"distribution: 'string'\" and a dictionary of parameters")
raise exceptions.ConfigurationError("Could not initialize {name}".format(
name = c.name(cls.__name__)
))
def configure(self):
self.campaign = Campaign.load(self.dataset, analyses=self.config)
if self.args.bias:
try:
log.info("Setting bias function discriminators")
discriminators = {
'apparent_magnitude': MagnitudeDiscriminator.from_config(self.bias.magnitude),
'altitude': AltitudeDiscriminator.from_config(self.bias.altitude),
'angular_speed': AngularSpeedDiscriminator.from_config(self.bias.angular_speed),
}
log.info(f"Loaded {c.num(len(discriminators))} discriminators:")
for discriminator in discriminators.values():
discriminator.log_info()
self.campaign.set_discriminators(discriminators)
except AttributeError as e:
raise exceptions.ConfigurationError(e) from e
else:
log.debug("No bias file set")