InvestigatorConnection#
- class cegalprizm.investigator.InvestigatorConnection(use_licensed_features: bool = False, hub_context: Optional[cegalprizm.hub.base_ctx.BaseContext] = None, hub_connection_parameters: Optional[cegalprizm.hub.connection_parameters.ConnectionParameters] = None)#
This class represents a connection to an instance of Investigator
The connection to Investigator will be made using Hub. It may be either:
local (on the same machine running Python)
remote (on a machine on the same network)
cloud (on a machine connected via the cloud)
The Investigator may be running as:
A plugin inside Petrel
A standalone investigator server
Functions
__init__([use_licensed_features, ...])Returns a list of the available investigations
Creates a investigation containing the iris dataset
investigation_from_dataframe(dataframe[, ...])Creates an investigation from the specified dataframe
investigation_from_file(path)Creates an investigation from the specified file
load_investigation([name, investigation_id])Loads the investigation via Hub
remove_investigation([name, investigation_id])This removes an investigation from the Investigator server
This will force the Hub connection to be reset
set_connector_labels(labels)Set specific connector labels to be used
- available_investigations() List[cegalprizm.investigator.named_tuples.InvestigationInfoTuple]#
Returns a list of the available investigations
- Raises
CegalHubError – if an unexpected error is reported by Hub
- Returns
A list of tuples containing the id and name for each available investigation
- Return type
List[InvestigationInfoTuple]
- create_iris_investigation() cegalprizm.investigator.inv.investigation.Investigation#
Creates a investigation containing the iris dataset
THe iris dataset is well know in data science and often used for examples.
- Raises
CegalHubError – if an unexpected error is reported by Hub
- Returns
An object representing the Iris investigation
- Return type
- investigation_from_dataframe(dataframe: pandas.core.frame.DataFrame, continuous_column_names: Optional[Sequence[str]] = None, continuous_column_info: Optional[Dict[str, cegalprizm.investigator.named_tuples.ContinuousDimensionInfoTuple]] = None, discrete_column_names: Optional[Sequence[str]] = None, dataset_column_name: Optional[str] = None, sample_index_column_names: Optional[Sequence[str]] = None) cegalprizm.investigator.inv.investigation.Investigation#
Creates an investigation from the specified dataframe
If none of the optional parameters as provided, then the “best” guess of how to represent the dataframe as an investigation will be used.
- Parameters
dataframe (pd.DataFrame) – The input dataframe
continuous_column_names (Sequence[str], optional) – a list of the dataframe column names to include in the investigation as continuous dimensions. Defaults to None.
continuous_column_info (Dict[str, ContinuousDimensionInfoTuple], optional) – a dictionary containing the ContinuousDimensionInfoTuple for each continuous dimension in the investigation. Defaults to None.
discrete_column_names (Sequence[str], optional) – a list of the dataframe column names to include in the investigation as discrete dimensions. Defaults to None.
dataset_column_name (str, optional) – a dataframe column name which should be used to identify different datasets. Defaults to None.
sample_index_column_names (Sequence[str], optional) – a list of the dataframe column names that identify sample index columns. The sample indices will be evaluated in the order of this list. Defaults to None.
- Raises
CegalHubError – if an unexpected error is reported by Hub
- Returns
An object representing the investigation
- Return type
- investigation_from_file(path: str) cegalprizm.investigator.inv.investigation.Investigation#
Creates an investigation from the specified file
- Parameters
path (str) – The path to the invpy file
- Raises
CegalHubError – if an unexpected error is reported by Hub
- Returns
An object representing the investigation
- Return type
- load_investigation(name: Optional[str] = None, investigation_id: Optional[str] = None) cegalprizm.investigator.inv.investigation.Investigation#
Loads the investigation via Hub
Note: Either the name or the investigation_id must be defined.
- Parameters
name (str, optional) – The name of the investigation to be loaded. Defaults to None.
investigation_id (str, optional) – The id of the investigation to be loaded. Defaults to None.
- Raises
CegalHubError – if an unexpected error is reported by Hub
ValueError – if the supplied parameters are both missing or if it is invalid
- Returns
An object representing the investigation
- Return type
- remove_investigation(name: Optional[str] = None, investigation_id: Optional[str] = None)#
This removes an investigation from the Investigator server
Removing the investigation will mean its data it can no longer be accessed and it will not be possible to create plots based on the investigation.
Note: Either the name or the investigation_id must be defined. Note: Removal of an investigation is immediate and cannot be reversed.
- Parameters
name (str, optional) – The name of the investigation to be removed. Defaults to None.
investigation_id (str, optional) – The id of the investigation to be removed. Defaults to None.
- Raises
CegalHubError – if an unexpected error is reported by Hub
ValueError – if the supplied parameters are both missing or if it is invalid
- renew_context()#
This will force the Hub connection to be reset
This should only be necessary if Hub is restarted or a new instance of Petrel is attached.
- set_connector_labels(labels: Dict[str, str])#
Set specific connector labels to be used
The supplied connector labels will be used as a filter to select the connector to be used for communication with Investigator. For example, labels can be used to target a specific Petrel instance when more than 1 instance available.
- Parameters
labels (Dict[str, str]) – A dictionary of key-value strings labels