def draw_referenced_subgraph(g, website_url, thank_you_page_url, since,
min_visited_count):
raw_graph = _build_networkx_graph(g, website_url, thank_you_page_url,
since)
persistent_nodes = [
node for node, attr in raw_graph.nodes(data=True)
if attr["label"] == "persistentId"
]
graph_with_pos_computed = drawing.layout(
raw_graph,
nx.shell_layout,
nlist=[[website_url],
[
node for node, attr in raw_graph.nodes(data=True)
if attr["label"] == "transientId"
],
[
node for node, attr in raw_graph.nodes(data=True)
if attr["label"] == "persistentId"
], [thank_you_page_url]])
# update positions and change node label
raw_graph.nodes[thank_you_page_url]["pos"] += (0, 0.75)
for node in persistent_nodes:
has_visited_thank_you_page = False
visited_at_least_X_times = False
for check_name, value in raw_graph.nodes[node]["visited_events"].items(
):
if ">=" in check_name and value > 0:
if "thank" in check_name:
has_visited_thank_you_page = True
elif value > min_visited_count:
visited_at_least_X_times = True
if (has_visited_thank_you_page or not visited_at_least_X_times):
for _, to in raw_graph.edges(node):
raw_graph.nodes[to]["opacity"] = 0.25
raw_graph.nodes[node]["opacity"] = 0.25
drawing.draw(
title=
"User devices that visited ecommerce websites and optionally converted",
scatters=[drawing.edges_scatter(graph_with_pos_computed)] + list(
drawing.scatters_by_label(graph_with_pos_computed,
attrs_to_skip=["pos", "opacity"],
sizes={
"transientId": 10,
"transientId-audience": 10,
"persistentId": 20,
"persistentId-audience": 20,
"website": 30,
"thankYouPage": 30,
})))
def draw_referenced_subgraph(g, transient_id):
graph = drawing.spring_layout(
_build_networkx_graph(
g,
g.V(transient_id).in_("has_identity").in_("member").next()))
drawing.draw(title="Single identity group graph structure",
scatters=[drawing.edges_scatter(graph)] + list(
drawing.scatters_by_label(graph,
attrs_to_skip=["pos"],
sizes={
"identityGroup": 60,
"transientId": 20,
"persistentId": 40
})),
annotations=drawing.edge_annotations(graph))
def show(g, website_id):
"""Show users that visited website on more than one device."""
transient_nodes_for_website = query_transient_nodes_for_website(
g, website_id)
website_node = query_website_node(g, website_id)
raw_graph = create_graph_for_website_and_transient_nodes(
website_node, transient_nodes_for_website)
graph = drawing.spring_layout(raw_graph)
drawing.draw(
title="",
scatters=[drawing.edges_scatter(graph)] +
list(drawing.scatters_by_label(graph, attrs_to_skip=["pos"])),
)
def draw_referenced_subgraph(g, root_url):
graph = _build_networkx_graph(
root_url,
query_results=_get_transient_ids(
_get_persistent_ids_which_visited_website(g, root_url),
root_url).next())
graph = drawing.layout(graph, nx.kamada_kawai_layout)
drawing.draw(
title="Brand interaction",
scatters=[drawing.edges_scatter(graph)] + list(
drawing.scatters_by_label(graph,
attrs_to_skip=["pos"],
sizes={
"websiteGroup": 30,
"transientId": 10,
"persistentId": 15,
"website": 10
})),
)
def draw_refrenced_subgraph(g, transient_id):
raw_graph = _build_networkx_graph(
g,
g.V(transient_id).in_("has_identity").in_("member").next())
graph_with_pos_computed = drawing.layout(raw_graph,
nx.spring_layout,
iterations=2500)
drawing.draw(
title="Part of single household activity on the web",
scatters=[drawing.edges_scatter(graph_with_pos_computed)] + list(
drawing.scatters_by_label(graph_with_pos_computed,
attrs_to_skip=["pos"],
sizes={
"identityGroup": 30,
"transientId": 15,
"persistentId": 20,
"websiteGroup": 15,
"website": 10
})),
)