Exploratory Data Analysis¶
Date published: 26/09/23
- bin.eda.calculate_metrics(G: Graph, output_dir: str) dict[float][source]¶
Calculate graph metrics.
- Args:
- G (nx.Graph):
The graph.
- output_dir (str):
The output directory for the visualisation.
- Returns:
- dict[float]:
The dictionary of metrics.
- bin.eda.construct_network(edge_list: DataFrame, from_col: str, to_col: str, len_component: int = 5) Graph[source]¶
Construct a graph from edge list data.
- Args:
- edge_list (pd.DataFrame):
The edge list.
- from_col (str):
The “from” column name.
- to_col (str):
The “to” column name.
- len_component (int, optional):
The minimum size of a subgraph to filter out. Defaults to 5.
- Returns:
- nx.Graph:
The constructed graph.
- bin.eda.log_results(tracking_uri: str, experiment_prefix: str, grn_name: str, edge_list_file: str, network_plot: str, metrics: dict[float]) None[source]¶
Log experiment results to the experiment tracker.
- Args:
- tracking_uri (str):
The tracking URI.
- experiment_prefix (str):
The experiment name prefix.
- grn_name (str):
The name of the GRN.
- edge_list_file (str):
The name of the edge list file.
- network_plot (str):
The path to the network plot to add as an artifact.
- metrics (dict[float]):
The dictionary of metrics.