sim_thresh

class virtualitics_sdk.nlp.sim_thresh.SimilarityThresholdExperiments(data_upload_step, advanced=False)

Bases: Step

logger = <Logger ReloadNetworkButton (WARNING)>

main_section = 'Similarity Threshold Experiments'

numeric_range_title = 'Similarity Threshold Slider'

run(flow_metadata, pyvip_client=None)

sim_thresh_step_description = "Perform multiple Knowledge Graph extractions with different candidate similarity thresholds and plot the extracted network's properties. "

step_title = 'Knowledge Graph Extraction'

virtualitics_sdk.nlp.sim_thresh.augment_nodes_with_extra_features(kg, store_interface)

Add extra features to a networkX graph. It uses the feature matrix and the feature names stored in the KG asset and the nlp features computed by the LanguageProcessor. Args:

kg: nx.Graph store_interface:

Returns:

kg: nx.Graph

virtualitics_sdk.nlp.sim_thresh.compute_relevant_entities(network_df, nlp_module, community)

virtualitics_sdk.nlp.sim_thresh.round_to_multiple(number, multiple)

virtualitics_sdk.nlp.sim_thresh.slider_callback(store_interface, pyvip_client=None)