def pca_is_ready(self, pca, **kwargs):
"""Checks whether a pca's status is FINISHED.
"""
check_resource_type(pca, PCA_PATH, message="A PCA id is needed.")
resource = self.get_pca(pca, **kwargs)
return resource_is_ready(resource)
def model_is_ready(self, model, **kwargs):
"""Checks whether a model's status is FINISHED.
"""
check_resource_type(model, MODEL_PATH, message="A model id is needed.")
resource = self.get_model(model, **kwargs)
return resource_is_ready(resource)
def ensemble_is_ready(self, ensemble):
"""Checks whether a ensemble's status is FINISHED.
"""
check_resource_type(ensemble, ENSEMBLE_PATH,
message="An ensemble id is needed.")
resource = self.get_ensemble(ensemble)
return resource_is_ready(resource)
def deepnet_is_ready(self, deepnet, **kwargs):
"""Checks whether a deepnet's status is FINISHED.
"""
check_resource_type(deepnet, DEEPNET_PATH,
message="A deepnet id is needed.")
resource = self.get_deepnet(deepnet, **kwargs)
return resource_is_ready(resource)
def logistic_regression_is_ready(self, logistic_regression, **kwargs):
"""Checks whether a logistic regressioin's status is FINISHED.
"""
check_resource_type(logistic_regression, LOGISTIC_REGRESSION_PATH,
message="A logistic regression id is needed.")
resource = self.get_logistic_regression(logistic_regression, **kwargs)
return resource_is_ready(resource)
def cluster_is_ready(self, cluster, **kwargs):
"""Checks whether a cluster's status is FINISHED.
"""
check_resource_type(cluster, CLUSTER_PATH,
message="A cluster id is needed.")
resource = self.get_cluster(cluster, **kwargs)
return resource_is_ready(resource)
def time_series_is_ready(self, time_series, **kwargs):
"""Checks whether a time series's status is FINISHED.
"""
check_resource_type(time_series, TIME_SERIES_PATH,
message="A time series id is needed.")
resource = self.get_time_series(time_series, **kwargs)
return resource_is_ready(resource)
def optiml_is_ready(self, optiml, **kwargs):
"""Checks whether an optiml's status is FINISHED.
"""
check_resource_type(optiml, OPTIML_PATH,
message="An optiml id is needed.")
resource = self.get_optiml(optiml, **kwargs)
return resource_is_ready(resource)
def fusion_is_ready(self, fusion, **kwargs):
"""Checks whether a fusion's status is FINISHED.
"""
check_resource_type(fusion, FUSION_PATH,
message="A fusion id is needed.")
resource = self.get_fusion(fusion, **kwargs)
return resource_is_ready(resource)
def anomaly_is_ready(self, anomaly, **kwargs):
"""Checks whether an anomaly detector's status is FINISHED.
"""
check_resource_type(anomaly,
ANOMALY_PATH,
message="An anomaly id is needed.")
resource = self.get_anomaly(anomaly, **kwargs)
return resource_is_ready(resource)
def dataset_is_ready(self, dataset):
"""Check whether a dataset' status is FINISHED.
"""
check_resource_type(dataset,
DATASET_PATH,
message="A dataset id is needed.")
resource = self.get_dataset(dataset)
return resource_is_ready(resource)
def topic_model_is_ready(self, topic_model, **kwargs):
"""Checks whether a topic model's status is FINISHED.
"""
check_resource_type(topic_model,
TOPIC_MODEL_PATH,
message="A topic model id is needed.")
resource = self.get_topic_model(topic_model, **kwargs)
return resource_is_ready(resource)
def source_is_ready(self, source):
"""Checks whether a source' status is FINISHED.
"""
check_resource_type(source,
SOURCE_PATH,
message="A source id is needed.")
source = self.get_source(source)
return resource_is_ready(source)
def linear_regression_is_ready(self, linear_regression, **kwargs):
"""Checks whether a linear regressioin's status is FINISHED.
"""
check_resource_type(linear_regression,
LINEAR_REGRESSION_PATH,
message="A linear regression id is needed.")
resource = self.get_linear_regression(linear_regression, **kwargs)
return resource_is_ready(resource)
def check_local_but_fields(model):
"""Whether the information in `model` is enough to use it locally
except for the fields section
"""
try:
return resource_is_ready(model) and \
check_model_structure(model)
except Exception:
return False
