prog_client#

The PaaS Sandbox Client (prog_client) is a python package for interacting with the PaaS Sandbox API. The class Session is used to create a connection to the API. The class methods are used to interact with the api, as described below:

class prog_client.Session(model, host='127.0.0.1', port=8555, **kwargs)#

Create a new Session in prog_server

Parameters

model (str) – The model to use for this session (e.g., batt)
host (str, optional) – Host address for PaaS Service. Defaults to ‘127.0.0.1’
port (int, optional) – Port for PaaS Service. Defaults to 5000.
model_cfg (dict, optional) – Configuration for ProgModel.
x0 (dict, optional) – Initial state for ProgModel.
load_est (str, optional) – Load estimator to use.
load_est_cfg (dict, optional) – Configuration for load estimator.
state_est (str, optional) – State Estimator to use (e.g., ParticleFilter). Class name for state estimator in progpy.state_estimators
state_est_cfg (dict, optional) – Configuration for state estimator.
pred (str, optional) – Prediction algorithm to use (e.g., MonteCarlo). Class name for prediction algorithm in progpy.predictors
pred_cfg (dict, optional) – Configuration for prediction algorithm.

Use:: session = prog_client.Session(**config)

get_event_state()#

Get the current event state

Returns

: float: Time of state estimate

UncertainData: Event state

Return type

tuple

get_model()#

Get the configured PrognosticsModel used by the session

Returns: configured PrognosticsModel used by the session
Return type: PrognosticsModel

Example

m = session.get_model()

get_output()#

Get the model output

Returns

: float: Time of state estimate

UncertainData: Model state

Return type

tuple

get_performance_metrics()#

Get current performance metrics

Returns

: float: Time of state estimate

UncertainData: Performance Metrics

Return type

tuple

get_predicted_event_state()#

Get the predicted event state

Returns

: float: Time of prediction

Prediction: predicted Event state

Return type

tuple

get_predicted_output()#

Get the predicted output

Returns

: float: Time of prediction

Prediction: predicted Event state

Return type

tuple

get_predicted_performance_metrics()#

Get predicted performance metrics

Returns

: float: Time of prediction

Prediction: Predicted performance Metrics

Return type

tuple

get_predicted_state()#

Get the predicted model state

Returns

: float: Time of prediction

Prediction: Predicted model state at save points

Return type

tuple

get_predicted_toe()#

Get the predicted Time of Event (ToE)

Returns

: float: Time of prediction

UncertainData: Prediction

Return type

tuple