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from __future__ import annotations
from networkx import DiGraph
from pandas import DataFrame
def get_cert_property(df: DataFrame, cert_id: int, column: str) -> str:
if column not in df.columns:
raise ValueError(f"Dataset does not have column '{column}'")
sub_df = df[df["cert_id"] == int(cert_id)]
if not sub_df.shape[0]: # Certificate is not in the dataset
raise ValueError(f"Cert ID: {cert_id} not in dataset")
if sub_df.shape[0] > 1: # There are more than one occurence with same ID
raise ValueError(f"Error Cert ID: {cert_id} has {sub_df.shape[0]} occurrences.")
return sub_df.iloc[0][column]
def get_fips_cert_references_graph(
df: DataFrame, cert_id: int, colour_mapper: dict[str, str]
) -> tuple[DiGraph, list[str]]:
if cert_id not in df["cert_id"].unique():
raise ValueError(f"Cert ID: {cert_id} is not in the dataset")
cert_id_series = df[df["cert_id"] == cert_id].iloc[0]
colour_map = [colour_mapper["chosen_cert_colour"]]
graph = DiGraph()
graph.add_node(cert_id)
# Display which certificates are directly referenced by the chosen certificate
for referenced_cert_id in cert_id_series["module_directly_referencing"]:
graph.add_node(referenced_cert_id)
graph.add_edge(cert_id, referenced_cert_id)
colour_map.append(colour_mapper["referencing_colour"])
# Display which certificates are directly referencing the chosen certificate
for referencing_cert_id in cert_id_series["module_directly_referenced_by"]:
graph.add_node(referencing_cert_id)
graph.add_edge(referencing_cert_id, cert_id)
colour_map.append(colour_mapper["referenced_colour"])
return graph, colour_map
def get_most_referenced_cert_graph(df: DataFrame, status_colour_mapper: dict[str, str]) -> tuple[DiGraph, list[str]]:
graph = DiGraph()
colour_map = []
max_referenced_by_num = df["incoming_direct_references_count"].max()
most_referenced_certificate = df[df["incoming_direct_references_count"] == max_referenced_by_num].iloc[0]
origin_cert_id: int = most_referenced_certificate["cert_id"]
origin_cert_status: str = most_referenced_certificate["status"]
graph.add_node(origin_cert_id)
colour_map.append(status_colour_mapper[origin_cert_status])
for cert_id_str in most_referenced_certificate["module_directly_referenced_by"]:
cert_id_int = int(cert_id_str)
graph.add_node(cert_id_int)
graph.add_edge(cert_id_int, origin_cert_id)
cert_status: str = get_cert_property(df, cert_id_int, "status")
colour_map.append(status_colour_mapper[cert_status])
return graph, colour_map
def get_most_referencing_cert_graph(df: DataFrame, status_colour_mapper: dict[str, str]) -> tuple[DiGraph, list[str]]:
graph = DiGraph()
colour_map = []
max_referencing_num = df["outgoing_direct_references_count"].max()
most_referencing_cert = df[df["outgoing_direct_references_count"] == max_referencing_num].iloc[0]
origin_cert_id = most_referencing_cert["cert_id"]
origin_cert_status = most_referencing_cert["status"]
colour_map.append(status_colour_mapper[origin_cert_status])
for cert_id_str in most_referencing_cert["module_directly_referencing"]:
cert_id_int = int(cert_id_str)
graph.add_node(cert_id_int)
graph.add_edge(origin_cert_id, cert_id_int)
cert_status: str = get_cert_property(df, cert_id_int, "status")
colour_map.append(status_colour_mapper[cert_status])
return graph, colour_map
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