pm4py.visualization.ocel.ocpn.variants.brachmann module

pm4py.visualization.ocel.ocpn.variants.brachmann.ot_to_color(ot: str) → str

Generates a deterministic hex color based on the object type string.

pm4py.visualization.ocel.ocpn.variants.brachmann.generate_dummy_id() → str

Generates a unique ID for a dummy node.

pm4py.visualization.ocel.ocpn.variants.brachmann.generate_arc_id(source_id: str, target_id: str) → str

Generates a unique ID for an arc.

pm4py.visualization.ocel.ocpn.variants.brachmann.get_neighbors(vertex_id: str, layout_data: Dict, direction: str) → List[str]

Gets upper (‘up’) or lower (‘down’) neighbors of a vertex.

pm4py.visualization.ocel.ocpn.variants.brachmann.get_arcs_between(u: str, v: str, layout_data: Dict) → List[Dict]

Gets arcs connecting vertex u and vertex v directly.

pm4py.visualization.ocel.ocpn.variants.brachmann.get_arcs_between_layers(layer_idx1: int, layer_idx2: int, layout_data: Dict) → List[Dict]

Gets all arcs connecting nodes between two specific layers.

pm4py.visualization.ocel.ocpn.variants.brachmann.is_incident_to_inner_segment(ocpn_layout: Dict, vertex_id: str) → bool

Checks if a vertex is a dummy node connected to another dummy node above it.

class pm4py.visualization.ocel.ocpn.variants.brachmann.OCPNGraph(layout_data: Dict)

Bases: object

Helper class to represent the graph for cycle breaking and layer assignment.

get_out_degree(node: str) → int

get_in_degree(node: str) → int

remove_node(node: str)

remove_nodes(nodes_to_remove: List[str])

get_sink() → str | None

get_source() → str | None

get_max_out_degree_node() → str | None

class pm4py.visualization.ocel.ocpn.variants.brachmann.Parameters(*values)

Bases: Enum

Parameters for the Sugiyama OCPN visualization

FORMAT = 'format'

BGCOLOR = 'bgcolor'

RANKDIR = 'rankdir'

ENGINE = 'engine'

ENABLE_GRAPH_TITLE = 'enable_graph_title'

GRAPH_TITLE = 'graph_title'

SOURCES = 'sources'

SINKS = 'sinks'

VERTEX_SEP = 'vertex_sep'

LAYER_SEP = 'layer_sep'

EDGE_SEP = 'edge_sep'

BORDER_PADDING = 'border_padding'

OBJECT_CENTRALITY = 'object_centrality'

OBJECT_ATTRACTION = 'object_attraction'

OBJECT_ATTRACTION_RANGE_MIN = 'object_attraction_range_min'

OBJECT_ATTRACTION_RANGE_MAX = 'object_attraction_range_max'

MAX_BARYCENTER_ITERATIONS = 'max_barycenter_iterations'

PLACE_RADIUS = 'place_radius'

TRANSITION_WIDTH = 'transition_width'

TRANSITION_HEIGHT = 'transition_height'

SILENT_TRANSITION_WIDTH = 'silent_transition_width'

ARC_SIZE = 'arc_size'

ARROWHEAD_SIZE = 'arrowhead_size'

INDICATE_ARC_WEIGHT = 'indicate_arc_weight'

INDICATE_VARIABLE_ARCS = 'indicate_variable_arcs'

VARIABLE_ARC_INDICATOR_COLOR = 'variable_arc_indicator_color'

VARIABLE_ARC_INDICATOR_SIZE = 'variable_arc_indicator_size'

TRANSITION_COLOR = 'transition_color'

TRANSITION_FILL_COLOR = 'transition_fill_color'

TRANSITION_TEXT_COLOR = 'transition_text_color'

DEFAULT_PLACE_COLOR = 'default_place_color'

ARC_DEFAULT_COLOR = 'arc_default_color'

TYPE_COLOR_MAPPING = 'type_color_mapping'

FONT_NAME = 'font_name'

FONT_SIZE = 'font_size'

pm4py.visualization.ocel.ocpn.variants.brachmann.apply(ocpn: Dict[str, Any], parameters: Dict[Any, Any] | None = None) → Digraph

Obtains a visualization of the provided object-centric Petri net using a Sugiyama-based layout algorithm.

Args:

ocpn (Dict[str, Any]): Object-centric Petri net structure. parameters (Optional[Dict[Any, Any]], optional): Algorithm parameters.

Returns:

Digraph: A Graphviz digraph object representing the layout.