def get_graph(
heu_net: HeuristicsNet,
parameters: Optional[Dict[Union[str, Parameters], Any]] = None
) -> pydotplus.graphviz.Dot:
"""
Gets a representation of an Heuristics Net
Parameters
-------------
heu_net
Heuristics net
parameters
Possible parameters of the algorithm, including:
- Parameters.FORMAT
Returns
------------
graph
Pydotplus graph
"""
if parameters is None:
parameters = {}
graph = pydotplus.Dot(strict=True)
graph.obj_dict['attributes']['bgcolor'] = 'transparent'
corr_nodes = {}
corr_nodes_names = {}
is_frequency = False
for node_name in heu_net.nodes:
node = heu_net.nodes[node_name]
node_occ = node.node_occ
graycolor = transform_to_hex_2(max(255 - math.log(node_occ) * 9, 0))
if node.node_type == "frequency":
is_frequency = True
n = pydotplus.Node(name=node_name,
shape="box",
style="filled",
label=node_name + " (" + str(node_occ) + ")",
fillcolor=node.get_fill_color(graycolor),
fontcolor=node.get_font_color())
else:
n = pydotplus.Node(
name=node_name,
shape="box",
style="filled",
label=node_name + " (" +
human_readable_stat(heu_net.sojourn_times[node_name]) +
")" if node_name in heu_net.sojourn_times else node_name +
" (0s)",
fillcolor=node.get_fill_color(graycolor),
fontcolor=node.get_font_color())
corr_nodes[node] = n
corr_nodes_names[node_name] = n
graph.add_node(n)
# gets max arc value
max_arc_value = -1
for node_name in heu_net.nodes:
node = heu_net.nodes[node_name]
for other_node in node.output_connections:
if other_node in corr_nodes:
for edge in node.output_connections[other_node]:
max_arc_value = max(max_arc_value, edge.repr_value)
for node_name in heu_net.nodes:
node = heu_net.nodes[node_name]
for other_node in node.output_connections:
if other_node in corr_nodes:
for edge in node.output_connections[other_node]:
this_pen_width = 1.0 + math.log(1 + edge.repr_value) / 11.0
repr_value = str(edge.repr_value)
if edge.net_name:
if node.node_type == "frequency":
e = pydotplus.Edge(
src=corr_nodes[node],
dst=corr_nodes[other_node],
label=edge.net_name + " (" + repr_value + ")",
color=edge.get_color(),
fontcolor=edge.get_font_color(),
penwidth=edge.get_penwidth(this_pen_width))
else:
e = pydotplus.Edge(
src=corr_nodes[node],
dst=corr_nodes[other_node],
label=edge.net_name + " (" +
human_readable_stat(repr_value) + ")",
color=edge.get_color(),
fontcolor=edge.get_font_color(),
penwidth=edge.get_penwidth(this_pen_width))
else:
if node.node_type == "frequency":
e = pydotplus.Edge(
src=corr_nodes[node],
dst=corr_nodes[other_node],
label=repr_value,
color=edge.get_color(),
fontcolor=edge.get_font_color(),
penwidth=edge.get_penwidth(this_pen_width))
else:
e = pydotplus.Edge(
src=corr_nodes[node],
dst=corr_nodes[other_node],
label=human_readable_stat(repr_value),
color=edge.get_color(),
fontcolor=edge.get_font_color(),
penwidth=edge.get_penwidth(this_pen_width))
graph.add_edge(e)
for index, sa_list in enumerate(heu_net.start_activities):
effective_sa_list = [n for n in sa_list if n in corr_nodes_names]
if effective_sa_list:
start_i = pydotplus.Node(name="start_" + str(index),
label="@@S",
color=heu_net.default_edges_color[index],
fontsize="8",
fontcolor="#32CD32",
fillcolor="#32CD32",
style="filled")
graph.add_node(start_i)
for node_name in effective_sa_list:
sa = corr_nodes_names[node_name]
if type(heu_net.start_activities[index]) is dict:
occ = heu_net.start_activities[index][node_name]
if occ >= heu_net.min_dfg_occurrences:
if is_frequency:
this_pen_width = 1.0 + math.log(1 + occ) / 11.0
if heu_net.net_name[index]:
e = pydotplus.Edge(
src=start_i,
dst=sa,
label=heu_net.net_name[index] + " (" +
str(occ) + ")",
color=heu_net.default_edges_color[index],
fontcolor=heu_net.
default_edges_color[index],
penwidth=this_pen_width)
else:
e = pydotplus.Edge(
src=start_i,
dst=sa,
label=str(occ),
color=heu_net.default_edges_color[index],
fontcolor=heu_net.
default_edges_color[index],
penwidth=this_pen_width)
else:
e = pydotplus.Edge(
src=start_i,
dst=sa,
label=heu_net.net_name[index],
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index])
else:
e = pydotplus.Edge(
src=start_i,
dst=sa,
label=heu_net.net_name[index],
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index])
graph.add_edge(e)
for index, ea_list in enumerate(heu_net.end_activities):
effective_ea_list = [n for n in ea_list if n in corr_nodes_names]
if effective_ea_list:
end_i = pydotplus.Node(name="end_" + str(index),
label="@@E",
color="#FFA500",
fillcolor="#FFA500",
fontcolor="#FFA500",
fontsize="8",
style="filled")
graph.add_node(end_i)
for node_name in effective_ea_list:
ea = corr_nodes_names[node_name]
if type(heu_net.end_activities[index]) is dict:
occ = heu_net.end_activities[index][node_name]
if occ >= heu_net.min_dfg_occurrences:
if is_frequency:
this_pen_width = 1.0 + math.log(1 + occ) / 11.0
if heu_net.net_name[index]:
e = pydotplus.Edge(
src=ea,
dst=end_i,
label=heu_net.net_name[index] + " (" +
str(occ) + ")",
color=heu_net.default_edges_color[index],
fontcolor=heu_net.
default_edges_color[index],
penwidth=this_pen_width)
else:
e = pydotplus.Edge(
src=ea,
dst=end_i,
label=str(occ),
color=heu_net.default_edges_color[index],
fontcolor=heu_net.
default_edges_color[index],
penwidth=this_pen_width)
else:
e = pydotplus.Edge(
src=ea,
dst=end_i,
label=heu_net.net_name[index],
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index])
else:
e = pydotplus.Edge(
src=ea,
dst=end_i,
label=heu_net.net_name[index],
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index])
graph.add_edge(e)
return graph
def apply(heu_net, parameters=None):
"""
Gets a representation of an Heuristics Net
Parameters
-------------
heu_net
Heuristics net
parameters
Possible parameters of the algorithm, including:
- Parameters.FORMAT
Returns
------------
gviz
Representation of the Heuristics Net
"""
if parameters is None:
parameters = {}
image_format = exec_utils.get_param_value(Parameters.FORMAT, parameters,
"png")
graph = pydotplus.Dot(strict=True)
graph.obj_dict['attributes']['bgcolor'] = 'transparent'
corr_nodes = {}
corr_nodes_names = {}
is_frequency = False
for node_name in heu_net.nodes:
node = heu_net.nodes[node_name]
node_occ = node.node_occ
graycolor = transform_to_hex_2(max(255 - math.log(node_occ) * 9, 0))
if node.node_type == "frequency":
is_frequency = True
n = pydotplus.Node(name=node_name,
shape="box",
style="filled",
label=node_name + " (" + str(node_occ) + ")",
fillcolor=node.get_fill_color(graycolor),
fontcolor=node.get_font_color())
else:
n = pydotplus.Node(name=node_name,
shape="box",
style="filled",
label=node_name,
fillcolor=node.get_fill_color(graycolor),
fontcolor=node.get_font_color())
corr_nodes[node] = n
corr_nodes_names[node_name] = n
graph.add_node(n)
# gets max arc value
max_arc_value = -1
for node_name in heu_net.nodes:
node = heu_net.nodes[node_name]
for other_node in node.output_connections:
if other_node in corr_nodes:
for edge in node.output_connections[other_node]:
max_arc_value = max(max_arc_value, edge.repr_value)
for node_name in heu_net.nodes:
node = heu_net.nodes[node_name]
for other_node in node.output_connections:
if other_node in corr_nodes:
for edge in node.output_connections[other_node]:
this_pen_width = 1.0 + math.log(1 + edge.repr_value) / 11.0
repr_value = str(edge.repr_value)
if edge.net_name:
if node.node_type == "frequency":
e = pydotplus.Edge(
src=corr_nodes[node],
dst=corr_nodes[other_node],
label=edge.net_name + " (" + repr_value + ")",
color=edge.get_color(),
fontcolor=edge.get_font_color(),
penwidth=edge.get_penwidth(this_pen_width))
else:
e = pydotplus.Edge(
src=corr_nodes[node],
dst=corr_nodes[other_node],
label=edge.net_name + " (" +
human_readable_stat(repr_value) + ")",
color=edge.get_color(),
fontcolor=edge.get_font_color(),
penwidth=edge.get_penwidth(this_pen_width))
else:
if node.node_type == "frequency":
e = pydotplus.Edge(
src=corr_nodes[node],
dst=corr_nodes[other_node],
label=repr_value,
color=edge.get_color(),
fontcolor=edge.get_font_color(),
penwidth=edge.get_penwidth(this_pen_width))
else:
e = pydotplus.Edge(
src=corr_nodes[node],
dst=corr_nodes[other_node],
label=human_readable_stat(repr_value),
color=edge.get_color(),
fontcolor=edge.get_font_color(),
penwidth=edge.get_penwidth(this_pen_width))
graph.add_edge(e)
for index, sa_list in enumerate(heu_net.start_activities):
effective_sa_list = [n for n in sa_list if n in corr_nodes_names]
if effective_sa_list:
start_i = pydotplus.Node(name="start_" + str(index),
label="@@S",
color=heu_net.default_edges_color[index],
fontsize="8",
fontcolor="#32CD32",
fillcolor="#32CD32",
style="filled")
graph.add_node(start_i)
for node_name in effective_sa_list:
sa = corr_nodes_names[node_name]
if type(heu_net.start_activities[index]) is dict:
if is_frequency:
occ = heu_net.start_activities[index][node_name]
this_pen_width = 1.0 + math.log(1 + occ) / 11.0
if heu_net.net_name[index]:
e = pydotplus.Edge(
src=start_i,
dst=sa,
label=heu_net.net_name[index] + " (" +
str(occ) + ")",
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index],
penwidth=this_pen_width)
else:
e = pydotplus.Edge(
src=start_i,
dst=sa,
label=str(occ),
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index],
penwidth=this_pen_width)
else:
e = pydotplus.Edge(
src=start_i,
dst=sa,
label=heu_net.net_name[index],
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index])
else:
e = pydotplus.Edge(
src=start_i,
dst=sa,
label=heu_net.net_name[index],
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index])
graph.add_edge(e)
for index, ea_list in enumerate(heu_net.end_activities):
effective_ea_list = [n for n in ea_list if n in corr_nodes_names]
if effective_ea_list:
end_i = pydotplus.Node(name="end_" + str(index),
label="@@E",
color="#",
fillcolor="#FFA500",
fontcolor="#FFA500",
fontsize="8",
style="filled")
graph.add_node(end_i)
for node_name in effective_ea_list:
ea = corr_nodes_names[node_name]
if type(heu_net.end_activities[index]) is dict:
if is_frequency:
occ = heu_net.end_activities[index][node_name]
this_pen_width = 1.0 + math.log(1 + occ) / 11.0
if heu_net.net_name[index]:
e = pydotplus.Edge(
src=ea,
dst=end_i,
label=heu_net.net_name[index] + " (" +
str(occ) + ")",
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index],
penwidth=this_pen_width)
else:
e = pydotplus.Edge(
src=ea,
dst=end_i,
label=str(occ),
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index],
penwidth=this_pen_width)
else:
e = pydotplus.Edge(
src=ea,
dst=end_i,
label=heu_net.net_name[index],
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index])
else:
e = pydotplus.Edge(
src=ea,
dst=end_i,
label=heu_net.net_name[index],
color=heu_net.default_edges_color[index],
fontcolor=heu_net.default_edges_color[index])
graph.add_edge(e)
file_name = tempfile.NamedTemporaryFile(suffix='.' + image_format)
file_name.close()
graph.write(file_name.name, format=image_format)
return file_name
def graphviz_visualization(
activities_count,
dfg,
measure="frequency",
max_no_of_edges_in_diagram=170,
start_activities=None,
end_activities=None,
):
"""
Do GraphViz visualization of a DFG graph
Parameters
-----------
activities_count
Count of attributes in the log (may include attributes that are not in the DFG graph)
dfg
DFG graph
image_format
GraphViz should be represented in this format
measure
Describes which measure is assigned to edges in direcly follows graph (frequency/performance)
max_no_of_edges_in_diagram
Maximum number of edges in the diagram allowed for visualization
Returns
-----------
node_edge_data
node and edge dict data
"""
if start_activities is None:
start_activities = []
if end_activities is None:
end_activities = []
# first, remove edges in diagram that exceeds the maximum number of edges in the diagram
dfg_key_value_list = []
for edge in dfg:
dfg_key_value_list.append([edge, dfg[edge]])
dfg_key_value_list = sorted(dfg_key_value_list, key=lambda x: x[1], reverse=True)
dfg_key_value_list = dfg_key_value_list[
0 : min(len(dfg_key_value_list), max_no_of_edges_in_diagram)
]
dfg_allowed_keys = [x[0] for x in dfg_key_value_list]
dfg_keys = list(dfg.keys())
for edge in dfg_keys:
if edge not in dfg_allowed_keys:
del dfg[edge]
activities_in_dfg = set()
activities_count_int = copy(activities_count)
for edge in dfg:
activities_in_dfg.add(edge[0])
activities_in_dfg.add(edge[1])
if len(activities_in_dfg) == 0:
activities_to_include = set(activities_count_int)
else:
activities_to_include = set(activities_in_dfg)
node_edge_data = {"nodes": [], "edges": []}
activities_map = {}
for act in activities_to_include:
if act in activities_count_int:
node_edge_data["nodes"].append(
{"data": {"id": act, "label": str(activities_count_int[act])}}
)
activities_map[act] = str(hash(act))
else:
node_edge_data["nodes"].append({"data": {"id": act, "label": None}})
activities_map[act] = str(hash(act))
# represent edges
for edge in dfg:
if "frequency" in measure:
label = str(dfg[edge])
else:
label = human_readable_stat(dfg[edge])
node_edge_data["edges"].append(
{"data": {"source": edge[0], "target": edge[1], "id": label}}
)
start_activities_to_include = [
act for act in start_activities if act in activities_map
]
end_activities_to_include = [act for act in end_activities if act in activities_map]
if start_activities_to_include:
node_edge_data["nodes"].append(
{"data": {"id": "start", "label": str(activities_count_int["start"])}}
)
for act in start_activities_to_include:
if "frequency" in measure:
node_edge_data["edges"].append(
{
"data": {
"source": "start",
"target": act,
"id": str(activities_count_int[act]),
}
}
)
else:
node_edge_data["edges"].append(
{"data": {"source": "start", "target": act, "id": None,}}
)
if end_activities_to_include:
node_edge_data["nodes"].append(
{"data": {"id": "end", "label": str(activities_count_int["start"])}}
)
for act in end_activities_to_include:
if "frequency" in measure:
node_edge_data["edges"].append(
{
"data": {
"source": act,
"target": "end",
"id": str(activities_count_int[act]),
}
}
)
else:
node_edge_data["edges"].append(
{"data": {"source": act, "target": "end", "id": None,}}
)
return node_edge_data